# ProphetStor Data Services, Inc. --- ## Pages - [Request Download: Why Fixed-Flow GPU Rack Cooling Wastes Energy](https://prophetstor.com/white-papers/why-fixed-flow-gpu-rack-cooling-wastes-energy/request-download/): Learn how Federator.ai Smart Liquid Cooling uses real-time metrics and variable-speed control to save up to 40% in cooling energy—without risking thermal limits. - [Request Download: Predictive Liquid Cooling for AI Data Centers](https://prophetstor.com/white-papers/predictive-liquid-cooling-for-ai-data-centers/request-download/): Save 30% cooling energy and boost GPU performance by 45% with Federator.ai Smart Liquid Cooling—predictive, workload-aware control for next-gen AI data centers. - [Request Download: Key Insight: "100% GPU Util" ≠ "100% Heat"](https://prophetstor.com/white-papers/why-100-gpu-utilization-doesnt-mean-100-heat/request-download/): ProphetStor uses real-time thermal and power metrics to optimize workload placement and cooling—enhancing efficiency beyond traditional GPU utilization indicators. - [Future-Proof AI Data Centers for AGI](https://prophetstor.com/future-proof-ai-data-centers-for-agi/): Federator.ai GPU Booster optimizes NVIDIA MIG technology, enhancing GPU utilization by up to 90% with detailed metrics and configuration recommendations. - [Resilient Cooling with Early Fault Detection](https://prophetstor.com/resilient-cooling-with-early-fault-detection/): Federator.ai GPU Booster optimizes NVIDIA MIG technology, enhancing GPU utilization by up to 90% with detailed metrics and configuration recommendations. - [Federator.ai Smart Liquid Cooling®](https://prophetstor.com/federator-ai-smart-liquid-cooling/): Federator.ai Smart Liquid Cooling cuts cooling energy by up to 30% in AI data centers while maintaining peak GPU performance and improving PUE. - [Request Download: Optimized Dynamic GPU Allocation in LLM Training](https://prophetstor.com/white-papers/optimized-dynamic-gpu-allocation-in-llm-training/request-download/): Discover how our technology and Kubernetes enhance efficiency, reduce costs, and promote sustainability through dynamic GPU resource allocation for AI and LLM training. - [Request Download: Smart Liquid Cooling: Beating Google on Efficiency](https://prophetstor.com/white-papers/ai-driven-data-center-cooling-google-vs-prophetstor/request-download/): Go beyond Google's AI for data center cooling—ProphetStor combines AI-driven resource management with smart liquid cooling to cut waste, boost performance, and meet ESG goals. - [Predictive Workload-Aware Liquid Cooling for High-Density AGI GPU Data Centers: Unlocking 30 Percent Energy Savings and 45 Percent Compute Acceleration](https://prophetstor.com/white-papers/predictive-liquid-cooling-for-ai-data-centers/): Save 30% cooling energy and boost GPU performance by 45% with Federator.ai Smart Liquid Cooling—predictive, workload-aware control for next-gen AI data centers. - [Proving Why 1.25-1.60 L min⁻¹ kW⁻¹ Is a Good Design Rule but Wasteful Without Variable-Speed Control](https://prophetstor.com/white-papers/why-fixed-flow-gpu-rack-cooling-wastes-energy/): Learn how Federator.ai Smart Liquid Cooling uses real-time metrics and variable-speed control to save up to 40% in cooling energy—without risking thermal limits. - [Key Insight: "100% GPU Util" ≠ "100% Heat"](https://prophetstor.com/white-papers/why-100-gpu-utilization-doesnt-mean-100-heat/): ProphetStor uses real-time thermal and power metrics to optimize workload placement and cooling—enhancing efficiency beyond traditional GPU utilization indicators. - [AI-Driven Data Center Cooling: Google vs. ProphetStor](https://prophetstor.com/white-papers/ai-driven-data-center-cooling-google-vs-prophetstor/): Go beyond Google's AI for data center cooling—ProphetStor combines AI-driven resource management with smart liquid cooling to cut waste, boost performance, and meet ESG goals. - [Efficient GPU Resource Management on Kubernetes](https://prophetstor.com/gpu-operations-on-kubernetes/): Federator.ai GPU Booster optimizes GPU resource allocation for LLM training workloads across Kubernetes platforms like Red Hat OpenShift, SUSE Rancher, and VMware Tanzu. - [Cloud Resource Optimization on Kubernetes](https://prophetstor.com/it-cloud-operations-on-kubernetes/): Federator.ai optimizes IT/Cloud resource allocation for IT operations across Kubernetes clusters on EKS, AKS, GKE, Red Hat OpenShift, and SUSE Rancher. - [Resource Optimization on Virtual Machines (VMs)](https://prophetstor.com/it-cloud-operations-on-virtual-machine-vm/): Federator.ai optimizes IT/Cloud resource allocation for IT operations across VM clusters on VMware vSphere, AWS EC2, Azure, and Google. - [ESG-Aligned Smart Cooling for AI Data Centers](https://prophetstor.com/esg-alignment-and-smart-cooling/): Federator.ai GPU Booster offers visibility into environmental metrics and will soon add air and liquid cooling metrics to ensure uninterrupted training and support ESG goals. - [Quick Adoption in AI Ecosystem](https://prophetstor.com/quick-adoption-in-ai-ecosystem/): Federator.ai Stack enables quick setup of Federator.ai GPU Booster with essential AI software components for AI/ML training, from platforms to driver downloads. - [AI/ML Throughput Enhancement](https://prophetstor.com/ai-ml-throughput-enhancement/): Federator.ai GPU Booster forecasts GPU needs for AI/ML workloads, reducing execution time by up to 50%, optimizing resources, and preventing training interruptions. - [GPU Utilization Optimization](https://prophetstor.com/gpu-utilization-optimization/): Federator.ai GPU Booster optimizes NVIDIA MIG technology, enhancing GPU utilization by up to 90% with detailed metrics and configuration recommendations. - [Prometheus](https://prophetstor.com/fgb-integrations/prometheus/): Federator.ai GPU Booster uses Prometheus for secure, agentless metrics collection, optimizing GPU resource planning for dynamic LLM training. - [Anton Prenneis](https://prophetstor.com/team/anton-prenneis/): Key roles in product management, strategic partnerships, and business development at IBM, EMC, and Dell. Leadership in startups focused on data analytics, AI, and renewable energy management. - [AI-Defined Data Center:
Federator.ai DataCenter OS for Optimal Efficiency, Sustainability, Automation, and Global Compute Platform Integration](https://prophetstor.com/white-papers/federator-ai-datacenter-os-for-addc/): Discover how Federator.ai DataCenter OS manages AI-driven data centers by virtualizing, visualizing, automating, and globalizing compute resources for efficient and proactive environmental management. - [Request Demo](https://prophetstor.com/request-demo-of-fgb/): Please fill out the form to the right to request a demo, and also check out our feature demo video and whitepapers for more information. We will contact you soon to schedule your demo. - [Demo Request Submitted](https://prophetstor.com/fgb-demo-request-submitted/): Your demo request for Federator. ai GPU Booster has been sent. Thank you for your interest in Federator. ai GPU... - [Federator.ai Stack®](https://prophetstor.com/federator-ai-gpu-booster/federator-ai-stack/): The Federator.ai Stack offers a comprehensive ecosystem that connects hardware, like GPU servers, with software, such as LLM applications, enabling the Federator.ai GPU Booster to run. - [Optimizing AI: The Critical Role of Dynamic GPU Resource Allocation in Large Language Model Training](https://prophetstor.com/white-papers/optimized-dynamic-gpu-allocation-in-llm-training/): Discover how our technology and Kubernetes enhance efficiency, reduce costs, and promote sustainability through dynamic GPU resource allocation for AI and LLM training. - [Federator.ai GPU Booster®](https://prophetstor.com/federator-ai-gpu-booster/): Enhance AI/ML training efficiency, optimize Kubernetes resources, boost total throughput, and reduce emissions in MultiTenant environments. - [Maximize GPU Efficiency in MultiTenant LLM Training: Federator.ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization](https://prophetstor.com/white-papers/maximizing-gpu-efficiency-in-multitenant-llm-training/): Discover how Federator.ai GPU Booster revolutionizes GPU optimization on high-end servers, slashing LLM training job times by 50% and doubling GPU utilization. - [Azure Virtual Machine](https://prophetstor.com/azure-virtual-machine/): Federator.ai optimizes operations on Azure Cloud with AI for performance and cost efficiency, tackling misconfiguration and over-provisioning. - [Federator.ai® & Microsoft Azure Monitor Integration](https://prophetstor.com/integrations/federator-ai-microsoft-azure-monitor-integration/): Federator.ai utilizes metrics from Azure Monitor to implement ML-based workload predictions and resource recommendations for VM clusters on Google Cloud. - [Google Compute Engine](https://prophetstor.com/google-compute-engine/): Federator.ai optimizes operations on Google Cloud with AI for performance and cost efficiency, tackling misconfiguration and over-provisioning. - [Federator.ai® & Google Cloud’s operations suite Integration](https://prophetstor.com/integrations/federator-ai-google-clouds-operations-suite-integration/): Federator.ai utilizes metrics from Google Cloud operetions suite to implement ML-based workload predictions and resource recommendations for VM clusters on Google Cloud. - [Federator.ai® & Amazon CloudWatch Integration](https://prophetstor.com/integrations/federator-ai-amazon-cloudwatch-integration/): Federator.ai utilizes metrics from Amazon CloudWatch to implement machine learning-based workload predictions and resource recommendations for VM clusters on AWS EC2. - [Federator.ai® & VMware vCenter Integration](https://prophetstor.com/integrations/federator-ai-vmware-vcenter-integration/): Federator.ai utilizes metrics from vCenter to implement machine learning-based workload predictions and resource recommendations for VM clusters on VMware vSphere. - [Taming MultiCloud Chaos: Leveraging Federator.ai for Simplified, Efficient, and Cost-Effective MultiCloud Management](https://prophetstor.com/white-papers/taming-multicloud-chaos/): Federator.ai enhances cost control, security config, and interoperability with a comprehensive view across platforms, enabling intelligent resource allocation and automation. - [VMware Tanzu](https://prophetstor.com/vmware-tanzu/): Popular Kubernetes Platform for VMs VMware Tanzu is a platform that enables organizations to build and run modern applications using... - [Red Hat OpenShift/ SUSE Rancher](https://prophetstor.com/red-hat-openshift-suse-rancher/): Popular Kubernetes Platforms Red Hat OpenShift and SUSE Rancher are two of the most popular enterprise-grade Kubernetes platforms used to... - [Amazon EKS/ Azure AKS/ Google GKE](https://prophetstor.com/amazon-eks-azure-aks-google-gke/): Popular Public Cloud Services Amazon EKS (Elastic Kubernetes Service), Azure AKS (Azure Kubernetes Service), and Google GKE (Google Kubernetes Engine)... - [VMware vSphere](https://prophetstor.com/vmware-vsphere/): Popular VM Platform VMware vSphere is a popular virtualization platform that provides a flexible infrastructure for running a wide range... - [Amazon EC2](https://prophetstor.com/amazon-ec2/): Federator.ai optimizes Amazon EC2 with AI for performance and cost efficiency, tackling misconfiguration and over-provisioning. - [Cyber Security Application](https://prophetstor.com/cyber-security-application/): Federator.ai provides comprehensive monitoring and analysis of data across various technology domains, including applications, infrastructure, data, network, and security. - [Optimal Portfolio of Cloud Instances](https://prophetstor.com/optimal-cloud-instance-combinations/): With the help of machine learning-based analysis, Federator.ai can classify workload patterns for individual applications in no time, after receiving historical data, and offer appropriate portfolios of cloud instances to fit application demands. - [Green IT/ ESG](https://prophetstor.com/green-it-esg/): 100% Green electricity and the adoption of Cloud resources are keys to lowering carbon footprint. Efficiency in cooling and consolidation of the servers make Data Center greener. - [Adding Application-Aware Optimization to VMware Tanzu Using ProphetStor Federator.ai's Patented Multi-Layer Correlation Technology](https://prophetstor.com/white-papers/adding-application-aware-optimization-to-vmware-tanzu/): A streamlined and optimized IT infrastructure is critical for success in today's competitive corporate world. - [CrystalClear by ProphetStor: Transforming Time Series Forecasting for Microservices Management](https://prophetstor.com/white-papers/crystalclear-by-prophetstor/): Explore why CrystalClear Time Series Analysis Engine, outperforming Facebook Prophet and LinkedIn Greykite, translates to more precise predictions, faster decision-making, and cost savings. - [Transforming IT and Cloud Operations with Federator.ai: Applied Observability and Deep Insights for Cybersecurity](https://prophetstor.com/white-papers/transforming-it-and-cloud-operations-with-federator-ai/): Enterprise CIOs face growing difficulties in managing complex IT and cloud operations while maintaining high levels of security and observability. - [Introduction to ProphetStor's Federator.ai: Cloud Operations, Optimized](https://prophetstor.com/white-papers/introduction-to-prophetstors-federator-ai/): ProphetStor is a leading provider of IT/cloud operation optimization and application resilience solutions, with over 14 granted USA patents and 10+ patents pending. - [Optimizing VMware Operation with AI-Powered Federator.ai: Boosting Efficiency, Performance, and Cost Savings in Virtual Infrastructure Management](https://prophetstor.com/white-papers/optimizing-vmware-operation-with-ai-powered-federator-ai/): Check out ProphetStor's Federator.ai, an AIOps platform designed to enhance your virtualization environment with predictive analytics and machine learning. - [The Patented AI-powered DataProphet Recommendation Engine is Revolutionizing Cloud Operations and Cost Management](https://prophetstor.com/white-papers/the-patented-ai-powered-dataprophet-recommendation-engine/): Explore how the DataProphet Recommendation Engine uses advanced machine learning algorithms to optimize performance, reduce costs, and improve efficiency. - [Unlocking the Power of Operation Metadata with Prometheus and Federator.ai: Easy and Efficient Predictive Analytics, Autoscaling, and Cost Management](https://prophetstor.com/white-papers/unlocking-the-power-of-operation-metadata-with-prometheus/): Prometheus and Federator.ai effectively manage IT systems with predictive analytics, application insight, autoscaling, and cost management for optimized operations. - [Optimizing VM Resources for Green IT: A Case Study with Chunghwa Telecom and ProphetStor Federator.ai](https://prophetstor.com/case-studies/a-case-study-with-chunghwa-telecom-and-prophetstor-federator-ai/): Explore how Chunghwa Telecom leveraged ProphetStor’s Federator.ai to overcome challenges of operations and achieve cost savings and Green IT objectives. - [How AWS Managed Service Providers Help Their Customer Optimize Cloud Spend and Improve Their Operation Margin with Federator.ai](https://prophetstor.com/white-papers/how-aws-msps-optimize-margin-and-customers-costs/): Discover how Federator.ai provides predictive analytics to help MSP and its end-users optimize usage of Amazon EC2 instances, leading to cost savings and improved performance. - [Federator.ai Significantly Reduces Cloud Spend and Carbon Footprint at P Bank](https://prophetstor.com/case-studies/federator-ai-significantly-reduces-cloud-spend-and-carbon-footprint-at-p-bank/): Explore how Federator.ai optimizes the infrastructure, enhances application resilience, reduces cloud costs, and achieves Green IT for P Bank. - [ProphetStor’s AI-Enabled Energy Efficiency and Planning Solution for Modern Data Centers](https://prophetstor.com/white-papers/innovative-ai-solution-for-data-centers/): Unleash the full potential of AI with Federator.ai's patented multi-layer correlation technology to boost ESG compliance and lower costs in data centers. - [How Federator.ai is Helping a Leading Networking Company Improve Cloud Resource Management](https://prophetstor.com/case-studies/federator-ai-helps-networking-company-manage-cloud-resources/): Discover how Federator.ai helped a networking hardware & software company effectively manage cloud resources and achieve over 80% in estimated cumulative savings. - [Case Studies](https://prophetstor.com/case-studies/): See how companies have transformed their Cloud journeys with the help of ProphetStor to achieve efficiency, cost savings, and performance upgrades. Browse now. - [Federator.ai Brings a Pleasant Journey of a World-leading Research and Advisory Company in Moving to MultiCloud with Kubernetes](https://prophetstor.com/case-studies/pleasant-journey-of-a-research-and-advisory-company-in-moving-to-multicloud/): Discover a research firm's successful move to MultiCloud and improved efficiency, cost savings, and performance with Federator.ai. - [A GPU-based Supercomputer Sees 60% Increase in Utilization with Federator.ai](https://prophetstor.com/case-studies/a-gpu-based-supercomputer-sees-60-increase-in-utilization/): See how Federator.ai helps a national-level super-computing center in Taiwan make an intelligent allocation to save up to 60% of resources. - [Orange Leverages Federator.ai for Automated Resource Management and Green IT to Meet EU Corporate Sustainability Regulations](https://prophetstor.com/case-studies/telecom-automates-resource-management-and-optimization-on-multicloud/): Learn how Orange optimized its resource management and automation with ProphetStor's MultiCloud solution to achieve cost savings and Green IT. - [Applied Observability with AI/ML Technologies — How Federator.ai Helps Modern IT Operations](https://prophetstor.com/federator-ais-ai-ml-technologies-for-the-future/): Unlock the potential of AI/ ML with ProphetStor’s Federator.ai which offers data management, Applied Observability and analytics solutions for biz to stay ahead in the game. - [Demo Request Submitted](https://prophetstor.com/demo-request-submitted/): Your demo request for Federator. ai has been sent. Thank you for your interest in Federator. ai. Before our team... - [Request Demo](https://prophetstor.com/request-demo/): Leave your contact information for us to schedule a demo by our engineers and see how Federtor.ai can help your business optimize both cost and performance KPIs. - [Contact Technical Support](https://prophetstor.com/contact-technical-support/): If you cannot get technical answers from our demo videos and documents, please fill out the form to the right and our senior engineer will contact you ASAP. - [Seminar/ Webinar Videos](https://prophetstor.com/seminar-webinar-videos/): It collects our presentation videos in seminars or webinars of the grand gathering. Federator.ai were introduced clearly and concisely to the elites in the industry. - [Intro/ Demo Videos](https://prophetstor.com/intro-demo-video/): The videos here contain an introduction to Federator.ai, a feature demo, reviews from clients, integration with other monitoring services, MSP strategy, etc. - [Setup Video](https://prophetstor.com/setup-video/): A quick video tutorial on installing Federator.ai from different sources and a step-by-step demo for the initial setup to have great management on Kubernetes. - [Go Green IT with Data-driven Intelligence](https://prophetstor.com/green-it-esg/): 100% Green electricity and the adoption of Cloud resources are keys to lowering carbon footprint. Efficiency in cooling and consolidation of the servers make Data Center greener. - [Application Acceleration](https://prophetstor.com/application-acceleration/): Based on predictions for individual application workload and resource usage, Federator.ai helps users achieve much better performance with fewer resources. - [Sound and Robust Sales Strategy for MSPs](https://prophetstor.com/optimal-cloud-instance-combinations/): With an innovative AI engine, Federator.ai provides visibility of cloud operations for an optimal blend of cloud instances to benefit MSP and its end-users. - [Efficient Microservice Resource Management with CrystalClear Time Series Analysis Engine](https://prophetstor.com/crystalclear-time-series-analysis-engine/): Tapping into time series metadata, CrystalClear Analysis Engine produces predictions with high accuracy to achieve operation metrics from corporate KPIs. - [DataProphet Recommendation Engine](https://prophetstor.com/dataprophet-recommendation-engine/): Based on the results from the AI-powered predictions, DataProphet Recommendation Engine provides Just-in-Time Fitted resource provision for operations. - [Cloud Cost Optimization and Application Resilience with ProphetStor](https://prophetstor.com/white-papers/cloud-cost-optimization-and-application-resilience-with-prophetstor/): Federator.ai uses ML technology and produces recommendations that meet and exceed Gartner framework for managing and optimizing costs of Public Cloud IaaS/PaaS. - [DataProphet: ProphetStor’s First-in-the-Industry Recommendation Engine for Cloud Operations Automation and Optimization](https://prophetstor.com/white-papers/first-in-the-industry-recommendation-engine-for-aiops/): Since there are too many application KPIs to understand and too many knobs to turn for optimization, a recommendation engine for AIOps is highly desired. - [ProphetStor’s CrystalClear Time Series Analysis Engine— Analytical Excellence Is All about Speed](https://prophetstor.com/white-papers/correlation-based-predictions/): The algorithm of prediction-based resource management is a novel concept that utilizes correlations for precise predictions with less resource & time consumption. - [Federator.ai®](https://prophetstor.com/federator_ai/): Federator.ai realizes AIOps by utilizing operation data for ML-based predictions and intelligently orchestrating application resources. Start for FREE! - [NGINX](https://prophetstor.com/integrations/nginx/): With autoscaling recommendation from Federator.ai, users can experience better performance in a more cost-efficient way for upstream web services on K8s. - [Ahim Kho](https://prophetstor.com/team/ahim-kho/): The Head of Business Development and Head of Partner Ecosystems at AWS, the Director of Marketing/Channel/Storage business at Sun Microsystems, VP at EMC, Managing Director at Bluecoat, President at Data Domain, Country Manager at Violin Memory, and Managing Director at Nutanix. - [Kafka](https://prophetstor.com/integrations/kafka-consumer-autoscaling/): Utilizing Machine Learning technology for predictions and analysis, Federator.ai achieves much better performance with much fewer resources by AI autoscaling. - [Prometheus](https://prophetstor.com/integrations/prometheus/): With the integration of Prometheus, Federator.ai analyzes the application and workload metrics and offers the workload predictions and resource recommendations. - [Sysdig](https://prophetstor.com/integrations/sysdig/): With the integration of Sysdig, Federator.ai analyzes the applications and workload metrics and provides the workload predictions and resource recommendations. - [Datadog](https://prophetstor.com/integrations/datadog/): By integrating with Datadog, Federator.ai can track and predict resource usage to prevent costly over-provisioning or performance-impacting under-provisioning. - [Federator.ai's Integrations](https://prophetstor.com/integrations/): Integration with existing monitoring services and Cloud platforms for fast adoption of ML-based automated solutions for optimization of cost and performance. - [SUSE/ Rancher Marketplace](https://prophetstor.com/suse-rancher-marketplace/): With Federator.ai, SUSE/ Rancher can benefit from the efficiency of capacity planning, continuous optimization of resource allocation, and cost savings. - [Cost Management and Cloud Migration](https://prophetstor.com/cost-management/): Federator.ai provides cost projection by workload predictions, operational savings with continuous rightsizing, and optimal migration scenarios for MultiCloud. - [Performance Optimization](https://prophetstor.com/performance-optimization/): Based on machine learning for the application-specific workload and KPI metrics, Federator.ai provides Just-in-Time Autoscaling to fit the application demands. - [Sysdig Integration](https://prophetstor.com/sysdig-integration/): Federator.ai is an AI-based solution that helps enterprise who uses Sysdig service manage, optimize, auto-scale resources for any applications on Kubernetes. - [Federator.ai Application Form](https://prophetstor.com/federator-ai-trial/): Submit the form for a free AIOps software download. An email with information on Federator.ai installation will be sent to you. Let’s start to optimize Cloud. - [Documentation](https://prophetstor.com/documentation/): Documentation for powerful AI-powered solutions for GPU and MultiCloud, including installation guides, user guides, and release notes for different versions. - [Federator.ai® Drastically Improves Cost and Performance of Kafka Running on Kubernetes](https://prophetstor.com/white-papers/federator-ai-drastically-improves-cost-and-performance-of-kafka-running-on-kubernetes/): Introduction A Kafka Stream Application reads data from a topic, performs calculations and transformations, and then writes the result back... - [Improving Cloud-Native Application KPIs with Multi-Layer Correlation and Prediction](https://prophetstor.com/white-papers/improving-cloud-native-application-kpis-with-multi-layer-correlation-and-prediction/): Federator.ai tackles how to adjust microservices to improve the application KPIs with ML-based Multi-Layer correlation, prediction, and application-aware HPA. - [How Federator.ai Optimizes Cost Savings for MultiCloud Deployments](https://prophetstor.com/white-papers/how-federator-ai-optimizes-cost-savings-for-multicloud-deployments/): Organizations waste 30 percent of cloud spend. It results from the lack of visibility and capability of cloud resources. The most cost-effective way for AIOps… - [Why Horizontal Pod Autoscaling in Kubernetes Needs to Be Application-Aware](https://prophetstor.com/white-papers/why-horizontal-pod-autoscaling-in-kubernetes-needs-to-be-application-aware/): Introduction The workloads running in Kubernetes clusters are characterized by their respective Key Performance Indicators (KPIs). To meet diverse, application-specific... - [Press Releases](https://prophetstor.com/press-releases-2/press-releases/): Press Releases 2024 2020 2023 2019 2022 2018 2021 2017 2024 2023 2022 2021 2020 2019 2018 2017 - [Legal](https://prophetstor.com/legal/): It includes ProphetStor Privacy Statement, which explains how ProphetStor collects/ uses/ discloses your information, and End User License Agreement (EULA). - [Eula Legal](https://prophetstor.com/legal/eula-legal/): ProphetStor End User License Agreement Last Updated: November 20, 2023 This End User License Agreement (“EULA”) is a legal contract... - [Press Releases](https://prophetstor.com/press-releases-2/): Announcements of new partnerships in the industry, a new release of the company’s flagship AIOps solution Federator.ai, and new clients adopting Federator.ai. - [Eric Chen](https://prophetstor.com/team/eric-chen/): Chen was the Vice President and General Manager of Asia Pacific Operations at FalconStor Software Inc. He holds a Ph.D. in computer and information science from Ohio State University and a B.S. in electrical engineering from National Taiwan University. - [Ming Sheu](https://prophetstor.com/team/ming-sheu/): Sheu holds a Ph.D. in computer and information science from Ohio State University and a B.S. in computer science and information engineering from National Taiwan University. - [Federator.ai® Integration With Data Monitoring – Datadog](https://prophetstor.com/kubernetes-monitoring-multicloud-hybrid-cloud-plaftorm/datadog/): Federator. ai® & Datadog Integration Datadog provides monitoring for servers, applications, and services. With Datadog, enterprise customers are able to... - [Datadog Integration](https://prophetstor.com/datadog-integration/): Federator.ai integration with Datadog to optimize application performance on Datadog dashboard and be available on Datadog Marketplace - [Home](https://prophetstor.com/): Based in Milpitas, CA, we specialize in IT/Cloud efficiency and GPU management, delivering advanced, resilient solutions with patented AI engines. --- ## Posts - [ProphetStor Data Services Secures Patent for AI-Powered Interactive Dashboard Technology](https://prophetstor.com/2024/12/23/patent-for-ai-powered-interactive-dashboard/): ProphetStor's patented AI interactive dashboard redefines infrastructure management with real-time insights, dynamic workflows, and seamless human-AI synergy. - [Video | ProphetStor Federator.ai GPU Booster Feature Demo](https://prophetstor.com/2024/06/26/federator-ai-gpu-booster-feature-demo/): ProphetStor Federator.ai GPU Booster optimizes GPU resources on Kubernetes with patented algorithms. Perfect for businesses using high-end NVIDIA GPUs, it streamlines GPU management, especially for MultiTenant AI model training. Maximize GPU utilization, boost training throughput, and keep your AI initiatives ahead with Federator.ai GPU Booster. - [ProphetStor and TOMORROW NET Forge Alliance to Boost AI Development and Deployment in Japan and Korea](https://prophetstor.com/2024/05/30/prophetstor-and-tomorrow-net-build-a-reseller-partnership/): ProphetStor has announced a reseller partnership with TOMORROW NET, a top Supermicro reseller, to transform GPU server use and sustainable computing in Japan and Korea. - [ProphetStor Awarded World’s First Patent for Spatial and Temporal Optimization of GPU Utilization](https://prophetstor.com/2024/05/23/worlds-first-patent-for-spatial-and-temporal-gpu-optimization/): ProphetStor received the world's 1st patent for Spatial and Temporal Optimization of GPU Utilization, a pioneering predictive analytics algorithm for AI/ML training. - [Federator.ai Solution Granted a Patent for Application-aware, Resilient, and Optimized IT/Cloud Operations](https://prophetstor.com/2023/02/15/federator-ai-solution-granted-patent-for-application-aware-resilient-and-optimized-it-cloud-operations/): ProphetStor is excited to announce the grant of US Patent No. 11579933 entitled "Method for Establishing System Resource Prediction and Resource Management Model through Multi-layer Correlations." - [Video | Win-Win Sales Strategy for An MSP and Its End-Users](https://prophetstor.com/2022/08/19/win-win-sales-strategy-for-msp-and-end-users/): Federator.ai helps achieve the balance of maximizing both the revenue for MSP and the cost savings for its end-users and earn more upsell opportunities for MSP. - [Industry-Leading Chunghwa Telecom Adopts ProphetStor Federator.ai for Green IT and Intelligent Continuous Cloud Operations](https://prophetstor.com/2022/07/15/cht-adopts-federator-ai-for-green-it-and-cloud-operations/): Chunghwa Telecom (CHT) has adopted ProphetStor Federator.ai in reducing idle resources in VM clusters and achieving both cost savings and Green IT objectives. - [ProphetStor Partners with Nextlink Technology to Exponentially Expand Managed Service Providers’ Businesses and Achieve Customer Obsession](https://prophetstor.com/2022/04/21/prophetstor-partners-with-nextlink/): Partnering with Nextlink, a leading managed MultiCloud solution provider in China, Taiwan, Hong Kong, and Southeast Asia, to facilitate cloud journey in APAC. - [Cloud Cost Management with ML-based Resource Predictions (Part II)](https://prophetstor.com/2022/04/13/cloud-cost-management-with-ml-based-resource-predictions-part-ii/): It offers the visibility of cloud spending at different resource levels (clusters, cluster nodes, namespaces, applications, containers), and reduces the cost. - [Cloud Cost Management with ML-based Resource Predictions (Part I)](https://prophetstor.com/2022/04/13/cloud-cost-management-with-ml-based-resource-predictions-part-i/): Federator.ai utilizes ML technologies as a unique approach to help companies solve the cloud overspending problem, which facilitates planning for cloud budget. - [Video | ProphetStor Federator.ai Feature Demo](https://prophetstor.com/2022/03/02/federator-ai-feature-demo-2/): ProphetStor Federator.ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for the applications on Kubernetes. - [ProphetStor Honors Sales and Technology Partner Evanston Technology Partners and Its CEO Emmanuel Jackson in Celebrating Black History Month](https://prophetstor.com/2022/02/11/prophetstor-partners-with-evanstontec/): We announce the onboarding of Evanston Technology Partners, which provides security, business intelligence and Cloud solutions, as a sales and technology partner. - [ProphetStor Releases Federator.ai 5.0 for Planning, Automation, and Optimization of The Next Phase Full-Scale Business-Focused Cloud Operations](https://prophetstor.com/2022/01/27/prophetstor-federator-ai-5-0/): Federator.ai 5.0 helps customers perform workload dynamics predictions and multi-layer impact analysis for a full-stack/deep understanding of applications. - [How to Configure An Application on Federator.ai for Autoscaling Kafka Consumer](https://prophetstor.com/2021/10/15/how-to-configure-an-application-on-federator-ai-for-autoscaling-kafka-consumer/): A quick description of how to achieve better performance and lower cost by auto-scaling Kafka consumers in Kubernetes environment, and a demo of how to configure an application on Federator.ai for Kafka consumer. - [Video | Kafka Summit Americas 2021 – Intelligent Auto-scaling of Kafka Consumers with Workload Prediction](https://prophetstor.com/2021/09/15/intelligent-auto-scaling-of-kafka-consumers-with-workload-prediction/): A presentation in Kafka Summit on why intelligent autoscaling is better than Kubernetes native HPA - [Intelligent Autoscaling of Kafka Consumers with Workload Prediction](https://prophetstor.com/2021/09/13/intelligent-autoscaling-of-kafka-consumers-with-workload-prediction/): Federator.ai calculates the right number of consumer replicas based on predicted workload and target KPI metrics to determine the capabilities of consumer pods. - [ProphetStor Federator.ai 4.7 Brings Machine Learning to Cloud Operation Optimization for VM and Container-Based Applications](https://prophetstor.com/2021/09/10/prophetstor-federator-ai-4-7/): Federator.ai 4.7 includes cost analysis and management, auto resource provisioning for applications, CICD integration, intelligent autoscaling, and free start. - [Installing Federator.ai from Red Hat Marketplace](https://prophetstor.com/2021/08/16/installing-federator-ai-from-red-hat-marketplace/): A quick tutorial on installing Federator.ai from Red Hat OpenShift Marketplace. - [Video | ProphetStor Federator.ai Optimizes Kubernetes for Cost and Performance](https://prophetstor.com/2021/07/27/federator-ai-optimizes-kubernetes-for-cost-and-performance/): Federator.ai uses predictive analytics to capture the dynamic application workloads and optimizes resource usage and performance in the MultiCloud environments. - [ProphetStor Joins Datadog Marketplace to Deliver AI-based Optimization and Automation for Cloud Native Applications](https://prophetstor.com/2021/07/19/prophetstor-joins-datadog-marketplace/): Federator.ai, an AIOps solution for optimization of performance and cost savings, is available on Datadog Marketplace. Start for FREE! - [A Smarter, Cost-efficient Way to Provision Cloud Workloads with ProphetStor Federator.ai](https://prophetstor.com/2021/07/02/a-way-to-provision-cloud-workloads-with-federator-ai/): Federator.ai is an AI-based solution that helps enterprises manage and optimize resources for applications on Kubernetes. - [Installing Federator.ai from SUSE/Rancher Marketplace](https://prophetstor.com/2021/06/30/installing-federator-ai-from-suse-rancher-marketplace/): A quick tutorial on installing Federator.ai from SUSE/Rancher Marketplace. - [Video | ProphetStor Federator.ai CI/CD Integration with Terraform](https://prophetstor.com/2021/06/16/federator-ai-for-terraform-video/): Learn how to integrate Federator.ai with Terraform to intelligently provision the right amount of resources to maximize the usage of their capacity. - [ProphetStor Partners with Padok to Help Customers to Optimize at All Stages of Their Journey in the Cloud](https://prophetstor.com/2021/06/11/prophetstor-partners-with-padok/): ProphetStor and Padok, a French Cloud solution company, become partners, that helps customers in EMEA achieve both application performance and cost objectives. - [Video | ProphetStor Federator.ai and Sysdig Integration](https://prophetstor.com/2021/05/31/federator-ai-for-sysdig-video/): Integrated with Sysdig, Federator.ai offers workload predictions and right-sized resource recommendations for K8s clusters and applications on Sysdig. - [INFOGRAPHIC | Federator.ai Multi-layer Correlation](https://prophetstor.com/2021/05/24/infographic-federator-ai-multilayer-correlation/): Value Proposition of Federator. ai Why Federator. ai Application behaviors are dynamic and optimization are hard, so ProphetStor Federator. ai... - [Video | ProphetStor Federator.ai and Datadog Integration](https://prophetstor.com/2021/05/18/federator-ai-for-datadog-video/): Integrated with Datadog, Federator.ai offers workload predictions and right-sized resource recommendations for K8s clusters and applications on Datadog. - [Video | ProphetStor Federator.ai Feature Demo](https://prophetstor.com/2022/03/02/federator-ai-feature-demo): ProphetStor Federator. ai Feature Demo With ProphetStor Federator. ai, you can easily manage, optimize, and auto-scale resources for any applications... - [ProphetStor Federator.ai Installation and Configuration](https://prophetstor.com/2021/04/20/federator-ai-installation-and-configuration/): ProphetStor Federator.ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for any applications on Kubernetes. Using advanced machine learning algorithms to predict application workloads, Federator.ai scales the appropriate amount of resources at the right time for optimized application performance. - [ProphetStor Brings Machine Learning-Based Intelligent Kubernetes Orchestration to Sysdig Customers and Simplified MultiCloud Cost Analysis with Federator.ai](https://prophetstor.com/2021/03/15/prophetstor-brings-intelligent-kubernetes-orchestration-to-sysdig-customers/): Federator.ai, an AIOps platform, collects operation metrics from Sysdig, a secure DevOps company, to achieve data-driven intelligence in a single-pane console. - [Joint webinar with Datadog:
Understanding and Rightsizing Container Resources With Datadog and Prophetstor](https://prophetstor.com/2021/02/26/joint-webinar-with-datadog/): In this webinar, we show how Datadog and ProphetStor help teams to solve the challenges in deploying containerized applications on OpenShift by bringing end-to-end visibility and resource optimization recommendations to meet application performance and cost requirements. - [INFOGRAPHIC | Federator.ai Multicloud AIOps](https://prophetstor.com/2021/02/19/infographic-federator-ai/): Prophetstor Federator.ai brings machine learning to make Kubernetes automated Application-Aware and Workload-Sensible, which can save your operation cost and improve applications performance at the same time. - [ProphetStor Brings Machine Learning-Based Intelligent Kubernetes Orchestration to Sysdig Customers](https://prophetstor.com/2021/02/09/prophetstor-federator-4-4-release/): The latest Federator.ai 4.4, including Spot instance recommendations for Multicloud cost analysis, is available to Sysdig customers - [INFOGRAPHIC | Fedemeter](https://prophetstor.com/2020/12/29/infographic-fedemeter/): Fedemeter, the patent-pending cost analysis module of Federator.ai, takes the input of current cluster configuration and workload prediction to produce a recommendation of the most cost-optimized cluster configuration for users. - [OpenShift TV program:
AI-Enabled Proactive Management for Cost and Performance Optimization in Hybrid MultiCloud](https://prophetstor.com/2020/12/21/openshift-tv-program-dec-16-2020/): Mike Waite, Senior Principal Product Marketing at Red Hat, interviewed ProphetStor CEO Eric Chen and EVP of Products Ming Sheu... - [ProphetStor Adds to Its Executive Business Development Team with Industry Veteran](https://prophetstor.com/2020/12/07/prophetstor-adds-to-its-executive-business-development-team/): Tad Lebeck has joined its executive team, which brings to ProphetStor more than 30 years of professional experience in enterprise software and cloud solution from Legato, Symantec, Veritas, and Huawei-Symantec, to name a few. - [ProphetStor Expands Taipei Operation to Support Its APAC Regional Customers](https://prophetstor.com/2020/11/25/prophetstor-expands-taipei-operation/): MILPITAS, CA, November 25, 2020 — ProphetStor is delighted to announce the opening of its new and expanded Taipei office... - [Joint webinar with Red Hat:
Federator.ai for Optimizing Resource Management on OpenShift](https://prophetstor.com/2020/11/11/joint-webinar-with-red-hat/): A joint webinar with Red Hat on how Federator. ai optimizes resource management on OpenShift. Watch webinar recording here: https://www.... - [See How ProphetStor Helps Orange France](https://prophetstor.com/2020/10/30/see-how-prophetstor-helps-orange-france/): The Interview with Manager of 'XaaS' Cloud Department at Orange. - [Video | Red Hat Summit 2019 - ProphetStor Federator.ai Demo](https://prophetstor.com/2020/09/15/video-red-hat-summit-2019-prophetstor-federator-ai-demo/): Red Hat Summit 2019 – ProphetStor Federator. ai Demo #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat, Tweet About ProphetStor Data... - [ProphetStor Announces Availability of Federator.ai on Red Hat Marketplace](https://prophetstor.com/2020/09/08/red-hat-marketplace/): ProphetStor's flagship solution Federator.ai, which uses advanced machine learning technologies, is now available through Red Hat Marketplace. - [ProphetStor Is Granted a Patent on Modeling Application Workloads to Automate the Management and to Predict the Anomalies of Storage Resources in MultiCloud Environments](https://prophetstor.com/2020/08/31/prophetstor-is-granted-a-patent-on-modeling-application-workloads-to-automate-the-management-and-to-predict-the-anomalies-of-storage-resources-in-multicloud-environments/): MILPITAS, CA, August 31, 2020 — ProphetStor Data Services, Inc. was assigned the patent “METHOD AND SYSTEM FOR STORAGE TRAFFIC... - [ProphetStor Brings Machine Learning Based Intelligent Kubernetes Orchestration to Datadog Customers](https://prophetstor.com/2020/08/24/prophetstor-brings-machine-learning-based-intelligent-kubernetes-orchestration-to-datadog-customers/): ProphetStor Data Services, Inc. today announced the general availability of Federator. ai 4. 3 for Datadog. Federator. ai, ProphetStor’s Artificial... - [ProphetStor Is Granted a Foundation Patent on Adapting Infrastructure Resource Deployments According to the Lifecycle of Application Workloads](https://prophetstor.com/2020/08/17/prophetstor-is-granted-a-foundation-patent-on-adapting-infrastructure-resource-deployments-according-to-the-lifecycle-of-application-workloads/): ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR DEPLOYING STORAGE SYSTEM RESOURCES WITH LEARNING OF WORKLOADS APPLIED THERETO“... - [ProphetStor’s Patent on Meeting Applications Future Demands Is the Foundation for Viable AIOps and Machine Learning for System Operation](https://prophetstor.com/2020/08/10/prophetstors-patent-on-meeting-applications-future-demands-is-the-foundation-for-viable-aiops-and-machine-learning-for-system-operation/): ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR OPTIMIZING STORAGE CONFIGURATION FOR FUTURE DEMAND AND SYSTEM THEREOF“ (Patent... - [ProphetStor’s Patent on AI-Powered Workload-Aware Framework Becomes the Foundation of AIOps for Optimization in MultiCloud and 5G](https://prophetstor.com/2020/08/03/prophetstors-patent-on-ai-powered-workload-aware-framework-becomes-the-foundation-of-aiops-for-optimization-in-multicloud-and-5g-2/): At the heart of the IT technology, it is the applications that need to be ultimately supported. ProphetStor brings the essence of workload awareness to its design philosophy for optimization in resource allocation and workload placement. - [ProphetStor Adds to Its Executive Team with Industry Veteran](https://prophetstor.com/2020/07/27/prophetstor-adds-to-its-executive-team-with-industry-veteran/): ProphetStor Data Services, Inc. has been striving to bring its AI-enabled solution to address the complexity and efficacy of the... - [ProphetStor’s Patent on AI-based Methods in Predicting the Life Span of Storage Systems Facilitates Proactive Management to Support SLAs and Reduce Operation Costs in Data and Cloud Centers](https://prophetstor.com/2020/07/20/prophetstors-patent-on-ai-based-methods-in-predicting-the-life-span-of-storage-systems-facilitates-proactive-management-to-support-slas-and-reduce-operation-costs-in-data-and-cloud-centers/): ProphetStor Data Services, Inc. was assigned the patent “METHOD AND SYSTEM FOR DIAGNOSING REMAINING LIFETIME OF STORAGES IN DATA CENTER“... - [Orange France Uses Federator.ai for Auto-scaling, Optimizing Resources and Application Performance on Its MultiCloud Infrastructure](https://prophetstor.com/2020/07/09/orange-france-uses-federator-ai-for-auto-scaling-optimizing-resources-and-application-performance-on-its-multi-cloud-infrastructure/): France Télécom S.A., the 4th largest mobile network operator in Europe, uses Federator.ai for auto-scaling, optimizing resources and application performance on its MultiCloud infrastructure. - [ProphetStor Joins Datadog Partner Network as a Technology Partner and Offers Integrated Intelligent Orchestration Solutions to Joint Customers](https://prophetstor.com/2020/06/24/prophetstor-joins-datadog-partner-network-as-a-technology-partner-and-offers-integrated-intelligent-orchestration-solutions-to-joint-customers/): The Federator.ai and Datadog integration allows customers to get AI-enabled recommendations for HPA based on observability into applications’ resource utilization. - [Federator.ai – AI Solution for Auto-Scaling on Kubernetes with Datadog](https://prophetstor.com/2020/06/17/federator-ai-ai-solution-for-auto-scaling-on-kubernetes-with-datadog/): Using metrics from Datadog, Federator.ai provides AI-based predictions to make recommendations and auto-scale containerized application workloads on Kubernetes. - [Democratizing Cloud Usage with Digital Intelligence for Multicloud](https://prophetstor.com/2019/10/24/democratizing-cloud-usage-with-digital-intelligence-for-multicloud/): Target Audience: Users of NetApp Kubernetes Services Desired Action After Reading Post: Sign up for free trials. Topic – How... - [Application-Aware Federator.ai for Kafka on Kubernetes Enhances Performance and Reduces Cost](https://prophetstor.com/2019/10/24/application-aware-federator-ai-for-kafka-on-kubernetes-enhances-performance-and-reduces-cost/): The fluctuation in creating/deleting Kafka consumers may not be effective and result in added lags (queue length), which is not desirable for the operation. AI/ML-based solution - [ProphetStor’s Federator.ai Operator Provides Intelligent Resource Optimization for Red Hat OpenShift Users in MultiCloud Environments](https://prophetstor.com/2019/05/08/prophetstor-federatorai-operator-provides-intelligence-for-openhift/): ProphetStor Data Services, Inc. has officially announced its Federator. ai Operator that is listed on OperatorHub. io and can be... - [Prophetstor Will Exhibit AIOps for Openshift Solution in Red Hat Summit 2019 in Boston](https://prophetstor.com/2019/05/03/prophetstor-will-exhibit-aiops-for-openshift-solution-in-red-hat-summit-2019-in-boston/): MILPITAS, CA, May 03, 2019 —ProphetStor Data Services, Inc. , the leader in Digital Intelligence for Multi-Cloud platforms is delighted... - [ProphetStor Awarded A New Patent in Extending Disk Life Span with Work Load Patterns to Optimize Cost of Operation in MultiCloud Environments](https://prophetstor.com/2019/05/03/prophetstor-is-granted-a-patent-on-modeling-application-workloads-to-automate-the-management-and-to-predict-the-anomalies-of-storage-resources-in-multicloud-environments-2/): MILPITAS, CA, May 03, 2019 — ProphetStor Data Services, Inc. , a leader in Digital Intelligence for MultiCloud platforms, was... - [Arrow Electronics Extends Data and Artificial Intelligence Portfolio with ProphetStor](https://prophetstor.com/2018/10/29/arrow-electronics-extends-data-and-artificial-intelligence-portfolio-with-prophetstor/): Paris, October 29, 2018 — Global technology provider Arrow Electronics and Intelligent Data Platform provider ProphetStor Data Services, Inc. ,... - [Disk Health Prediction for Ceph Mimic](https://prophetstor.com/2018/09/24/disk-health-prediction-for-ceph-mimic/): MILPITAS, CA, September 24, 2018 — We at ProphetStor Data Services, Inc. are excited to announce our contribution to Ceph’s... - [Lanner Partners with ProphetStor](https://prophetstor.com/2018/09/21/lanner-partners-with-prophetstor-to-deploy-ai-based-predictive-maintenance-service-for-vcpe-ucpe/): Lanner Partners with ProphetStor to Deploy AI-based Predictive Maintenance Service for vCPE/uCPE Fremont, USA, September 21, 2018 — Lanner Electronics... - [First AI-Driven All Flash Array Customer in United Kingdom, Kennedy Wilson](https://prophetstor.com/2018/04/23/prophetstor-announces-its-first-ai-driven-all-flash-array-customer-in-united-kingdom-kennedy-wilson/): ProphetStor Announces its First AI-Driven All Flash Array Customer in United Kingdom, Kennedy Wilson MILPITAS, CA, April 23, 2018 —... - [AI-enabled Disk Prophet® Paves the Way for Intelligent Data Center Operations](https://prophetstor.com/2018/04/16/ai-enabled-disk-prophet-paves-the-way-for-intelligent-data-center-operations/): ProphetStor’s New AI-enabled Disk Prophet™ Paves the Way for Intelligent Data Center Operations MILPITAS, CA, April 16, 2018 — ProphetStor... - [ProphetStor Partnership with Peering one](https://prophetstor.com/2018/04/14/prophetstor-partnership-with-peering-one/): KUALA LUMPR, MALAYSIA, April 03, 2018 — ProphetStor Data Services, Inc. , a leader in Intelligent data platform, today announced... - [AI-Driven DiskProphet®2.0](https://prophetstor.com/2018/02/27/ai-driven-diskprophet2-0/): ProphetStor’s AI-Driven DiskProphet® 2. 0 Leaps to Deliver Higher Standard of Services with Accurate Predictions for Both Disks and Systems... - [Workload-consumed Resource Management in a Cloud Data Center](https://prophetstor.com/2018/01/16/workload-consumed-resource-management-in-a-cloud-data-center/): ProphetStor Strengthens Its Global Patent Portfolio with AI-enabled Predictives for Optimizing Utilization of the Workload-Consumed Resource Management in a Cloud... - [ProphetStor Patent Aims to Simplify Ai-driven Container Intelligence for Self-Driving Data Center](https://prophetstor.com/2018/01/04/prophetstor-patent-aims-to-simplify-ai-driven-container-intelligence-for-self-driving-data-center/): ProphetStor Patent Aims to Simplify AI-Driven Container Intelligence for Self-Driving Data Center MILPITAS, CA, January 04, 2018 — ProphetStor Data... - [XSKY and ProphetStor Team Up In Strategic Partnership in Beijing](https://prophetstor.com/2017/12/01/xsky-and-prophetstor-team-up-in-strategic-partnership-in-beijing/): BEIJING, CHINA, December 1, 2017 — XSKY Beijing Data Technology Corporation Limited and ProphetStor Data Services, Inc signed a strategic... - [StellarFlash Arrays Delivers Intelligence to Software-defined Datacenter](https://prophetstor.com/2017/09/18/stellarflash-arrays-delivers-intelligence-to-software-defined-datacenter/): To Satisfy the Changing Needs of Business-Critical Applications MILPITAS, CA, September 18, 2017 — ProphetStor Data Services, Inc. , the... - [ProphetStor Germany Go-to-market with Delivering Intelligence to Software-Defined Datacenter](https://prophetstor.com/2017/09/15/prophetstor-germany-go-to-market-with-delivering-intelligence-to-software-defined-datacenter/): First Appearance in Cloud 2017 Technology and Services Conference in Munich, Cologne and Hamburg PARIS, FRANCE. , September 15, 2017... - [ProphetStor Announces Distribution Agreement with Info X Distribution to Promote Ai-empowered StellarFlash](https://prophetstor.com/2017/08/09/prophetstor-announces-distribution-agreement-with-info-x-distribution-to-promote-ai-empowered-stellarflash/): The new distribution agreement is expected to strongly expand ProphetStor’s presence in North America MILPITAS, CA. , August 09, 2017... - [ProphetStor Drives EMEA Expansion with Key Strategic Appointments in France, UK And Germany](https://prophetstor.com/2017/07/11/prophetstor-drives-emea-expansion-with-key-strategic-appointments-in-france-uk-and-germany/): Next phase of company’s aggressive expansion strategy kicks off with the opening of EMEA offices with key appointments of Guillaume... - [Data Security Solutions to Safeguard Against Ransomware by HPE, ProphetStor & Innovix](https://prophetstor.com/2017/05/29/data-security-solutions-to-safeguard-against-ransomware-by-hpe-prophetstor-innovix/): ProphetStor and Innovix Distribution to introduce the Latest Innovation of Data Security to Safeguard against Ransomware MALAYSIA, KUALA LUMPUR, May... - [DR Prophet® Safeguards Enterprises Against Ransomware](https://prophetstor.com/2017/05/22/dr-prophet-safeguards-enterprises-against-ransomware/): ProphetStor DR Prophet® Safeguards Enterprises against Ransomware with Assured Recovery and Enhanced Protection Policy MILPITAS, CA, May 22, 2017 –... - [AI Holdings Invested US$10 Million to Expand Business in Japan](https://prophetstor.com/2017/02/17/ai-holdings-invested-us10-million-to-expand-business-in-japan/): Ai Holdings Corporation Makes US$10 Million Investment and Joins Forces with ProphetStor to Expand Business in Japan ProphetStor Data Services,... --- # # Detailed Content ## Pages > Learn how Federator.ai Smart Liquid Cooling uses real-time metrics and variable-speed control to save up to 40% in cooling energy—without risking thermal limits. - Published: 2025-06-20 - Modified: 2025-06-20 - URL: https://prophetstor.com/white-papers/why-fixed-flow-gpu-rack-cooling-wastes-energy/request-download/ - 頁面分類: Whitepapers - Folder: Whitepapers Request Download --- > Save 30% cooling energy and boost GPU performance by 45% with Federator.ai Smart Liquid Cooling—predictive, workload-aware control for next-gen AI data centers. - Published: 2025-06-17 - Modified: 2025-06-17 - URL: https://prophetstor.com/white-papers/predictive-liquid-cooling-for-ai-data-centers/request-download/ - 頁面分類: Whitepapers - Folder: Whitepapers Request Download --- > ProphetStor uses real-time thermal and power metrics to optimize workload placement and cooling—enhancing efficiency beyond traditional GPU utilization indicators. - Published: 2025-06-04 - Modified: 2025-06-04 - URL: https://prophetstor.com/white-papers/why-100-gpu-utilization-doesnt-mean-100-heat/request-download/ - 頁面分類: Whitepapers - Folder: Whitepapers Request Download --- > Federator.ai GPU Booster optimizes NVIDIA MIG technology, enhancing GPU utilization by up to 90% with detailed metrics and configuration recommendations. - Published: 2025-05-26 - Modified: 2025-06-19 - URL: https://prophetstor.com/future-proof-ai-data-centers-for-agi/ As artificial general intelligence (AGI) development accelerates, data centers must evolve to handle soaring thermal loads, fluctuating GPU demands, and dynamic AI workloads—all while meeting uptime and sustainability goals. Federator. ai GPU Booster and Smart Liquid Cooling provide a unified software coordination layer that bridges IT operations (deciding when and where to run GPU-intensive jobs) with OT infrastructure (managing cooling, energy, and thermal stability). This AI-defined approach ensures intelligent, real-time optimization across compute, thermal, and energy domains—preparing your data center for AGI-scale performance and operational resilience. Adaptive Cooling OptimizationDynamically adjusts chillers, liquid coolant pumps, valves, and other actuators in anticipation of compute workloads, enabling proactive and intelligent cooling control. GPU Rack-level Energy Optimization Identifies underutilized servers across racks using predictive workload analytics, then consolidates active workloads and hibernates inactive servers to reduce power and cooling needs at the rack level. GPU Server-Level Performance OptimizationMaximizes GPU utilization on each server through predictive analytics and dynamic scheduling, ensuring optimal resource allocation for MultiTenant workloads and significantly reducing LLM training completion time. Read More AI-Defined Data Center: Federator. ai DataCenter OS for Optimal Efficiency, Sustainability, Automation, and Global Compute Platform Integration Whitepaper Predictive Workload-Aware Liquid Cooling for High-Density AGI GPU Data Centers: Unlocking 30 Percent Energy Savings and 45 Percent Compute Acceleration Whitepaper Maximize GPU Efficiency in MultiTenant LLM Training: Federator. ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization Whitepaper --- > Federator.ai GPU Booster optimizes NVIDIA MIG technology, enhancing GPU utilization by up to 90% with detailed metrics and configuration recommendations. - Published: 2025-05-26 - Modified: 2025-06-02 - URL: https://prophetstor.com/resilient-cooling-with-early-fault-detection/ AI infrastructure must operate continuously under high thermal and computational loads. Unplanned thermal spikes, pump failures, or flow disruptions can lead to GPU throttling or even job termination—undermining service-level objectives in mission-critical environments. Federator. ai Smart Liquid Cooling continuously monitors GPU power, coolant flow, and thermal response in real time. It delivers early alerts, allowing operators to resolve issues before they impact workload performance. This proactive approach enhances uptime, protects hardware, and ensures seamless AI/ML operations. Real-Time Telemetry and Anomaly Detection Continuously collects high-frequency telemetry from GPUs, CDUs, and cooling systems to identify early signs of thermal stress, abnormal flow patterns, or rising ΔT—enabling timely alerts and preventive actions before failures impact operations. Predictive Fault Detection with AI Modeling Use historical workload patterns, thermal behavior, and pump dynamics to forecast potential failures or thermal bottlenecks, enabling preventive maintenance and thermal risk mitigation. Intelligent Escalation and Policy Triggers Integrate alerts into existing DCIM or BMS platforms to trigger automated responses—such as rerouting workloads, adjusting cooling profiles, or notifying support teams—ensuring service continuity even under stress. Read More AI-Driven Data Center Cooling: Google vs. ProphetStor Whitepaper Key Insight: “100% GPU Util” ≠ “100% Heat” Whitepaper Proving Why 1. 25-1. 60 L min⁻¹ kW⁻¹ Is a Good Design Rule but Wasteful Without Variable-Speed Control Whitepaper --- > Federator.ai Smart Liquid Cooling cuts cooling energy by up to 30% in AI data centers while maintaining peak GPU performance and improving PUE. - Published: 2025-05-26 - Modified: 2025-06-02 - URL: https://prophetstor.com/federator-ai-smart-liquid-cooling/ Overview Federator. ai Smart Liquid Cooling (SLC) transforms the way modern AI data centers manage thermal efficiency by shifting from static, wasteful cooling to intelligent, workload-aware thermal optimization. Built to support high-density GPU infrastructure, this advanced solution dynamically adjusts liquid flow based on predictive heat modeling, not just simplistic GPU utilization metrics. Integrated seamlessly with Supermicro SCC and other standards-compliant infrastructure controllers, Federator. ai Smart Liquid Cooling enables continuous cooling optimization that conserves energy, preserves hardware lifespan, and accelerates AI performance. Advanced Technologies Behind Federator. ai Smart Liquid Cooling is powered by a patented Multi-Layer Correlation Engine and a workload-sensitive control system that tightly couples AI workload telemetry with real-time hardware actuation. Smarter Cooling with Correlated Insights The patented AI engine treats every AI workload as a chain of interlocking events across layers, enabling per-workload correlation with resource usage and infrastructure metrics to predict GPU load changes. Workload-Aware Thermal Forecasting Proactively predicts GPU rack heat load 30–60 seconds in advance by analyzing GPU board power, utilization trends, Kubernetes job metadata, and ambient conditions. Intelligent Pump Speed Control for Energy Savings AI-powered cooling adjusts pump speeds to maintain the temperature difference (ΔT) between inlet and outlet coolant within the ideal 8–15 °C range, cutting pump energy use by up to 70% during low-power periods. Closed-Loop Integration with Supermicro SCC Bi-directional observability and control, using Prometheus and SCC API to collect GPU power/temperature/flow metrics and actuate optimized pump/valve responses. Benefits of Federator. ai Smart Liquid Cooling Up to 30% Cooling Energy Savings Adaptive... --- > Discover how our technology and Kubernetes enhance efficiency, reduce costs, and promote sustainability through dynamic GPU resource allocation for AI and LLM training. - Published: 2025-05-23 - Modified: 2025-05-23 - URL: https://prophetstor.com/white-papers/optimized-dynamic-gpu-allocation-in-llm-training/request-download/ - 頁面分類: Whitepapers - Folder: Whitepapers Request Download --- > Go beyond Google's AI for data center cooling—ProphetStor combines AI-driven resource management with smart liquid cooling to cut waste, boost performance, and meet ESG goals. - Published: 2025-05-23 - Modified: 2025-05-23 - URL: https://prophetstor.com/white-papers/ai-driven-data-center-cooling-google-vs-prophetstor/request-download/ - 頁面分類: Whitepapers - Folder: Whitepapers Request Download --- > Save 30% cooling energy and boost GPU performance by 45% with Federator.ai Smart Liquid Cooling—predictive, workload-aware control for next-gen AI data centers. - Published: 2025-05-19 - Modified: 2025-06-17 - URL: https://prophetstor.com/white-papers/predictive-liquid-cooling-for-ai-data-centers/ - 頁面分類: Whitepapers - Folder: Whitepapers Executive Summary Generative-AI clusters already impose rack heat loads above 130 kW and are projected to reach 200 kW in the next server refresh. Operating liquid loops at the Open Compute Project (OCP) design midpoint, approximately 1. 5 L min⁻¹ kW⁻¹, protects silicon at peak power but wastes up to 70 percent of pump energy during normal power valleys and cannot react fast enough to millisecond-scale spikes. Federator. ai Smart Liquid Cooling (SLC) eliminates this inefficiency. Its patented Multi-Layer Correlation engine (U. S. Patent 11 579 933) blends 10 Hz NVIDIA DCGM power data, rack-level ΔT and flow, and forthcoming Kubernetes job metadata captured by scheduler extenders. The SLC publishes a heat-index forecast on every control cycle and a corresponding pump-and-valve set-point. Any standards-compliant liquid-cooling controller, such as Supermicro SuperCloud Composer (SCC), Vertiv Environet, or another BMS. accepts the recommendation only after leak alarms are clear and vendor slew limits are respected (± 3 percent RPM min⁻¹, ≤ 10 percent valve travel min⁻¹). Measured resultsEnergy efficiencyPump energy reduced by 25–30 percent. Chiller and dry-cooler energy reduced by ≈ 5 percent. GPU junction temperature held at ≤ 83 °C. Capacity and accelerationOn a 5 GW AI campus, the released headroom is approximately 100 MW, equal to about 1 TWh and ≈125 million USD per year, or sufficient to power ≈ 5,700 additional GB-class racks without a new utility feed. When SLC is combined with Federator. ai GPU Booster, which increases active-rack utilization from 55 to 85 percent, overall compute throughput rises... --- > Learn how Federator.ai Smart Liquid Cooling uses real-time metrics and variable-speed control to save up to 40% in cooling energy—without risking thermal limits. - Published: 2025-05-07 - Modified: 2025-06-20 - URL: https://prophetstor.com/white-papers/why-fixed-flow-gpu-rack-cooling-wastes-energy/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon 1. OCP Guidelines and the rationale behind them Large-frame mechanical designers select pipe diameters, quick-disconnects, and pump heads for the worst-case rack TDP—e. g. , 120 kW for an NVIDIA GB200 NVL72 rack or 160 kW for coming Rubin racks. The Open Compute Project’s liquid-cooling guidance and vendor reference designs all embed the same sizing constant: Source Sizing rule Purpose OCP OAI Liquid-Cooling Guidelines (v1. 0) – §3. 2 1. 5 L min⁻¹ kW⁻¹ at ΔT ≤ 10 °CCold-plate loop design, any OAM-B or GB200 server. (Seamless heat transfer in liquid cooling solutions - Stulz) OCP Reservoir & Pumping Unit Spec (Meta/CoolIT) 150 L min⁻¹ for a 100 kW rack (≈ 1. 5 L min⁻¹ kW⁻¹)Defines the minimum pump curve for rack CDUs. Vertiv 360AI Ref-Design #020 (GB200 rack) 1. 35 L min⁻¹ kW⁻¹; dual VFD pumpsRow CDU supports 130 kW racks. nVent / Stulz CDU datasheets Variable-speed pumps sized at 1. 2–1. 4 L min⁻¹ kW⁻¹Advertise energy savings at part load. 1. 5 L min⁻¹ kW⁻¹ guarantees a ≤10 °C coolant rise when every Blackwell GPU in the rack is pinned at its 1 kW TDP and fans are bypassed. This keeps silicon Tjunction comfortably below 85 °C, satisfying NVIDIA spec. (GB200 NVL72 | NVIDIA)Pipe friction and quick-disconnect impedance limit practical ΔP; most RPU specs top out at 40 psi. Staying near 1. 5 L min⁻¹ kW⁻¹ balances flow and pressure head across dozens of cold plates. (CyberCool CMU | STULZ) 2. Real racks almost never run at... --- > ProphetStor uses real-time thermal and power metrics to optimize workload placement and cooling—enhancing efficiency beyond traditional GPU utilization indicators. - Published: 2025-05-06 - Modified: 2025-07-01 - URL: https://prophetstor.com/white-papers/why-100-gpu-utilization-doesnt-mean-100-heat/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon What "GPU Util" Actually Measures When NVIDIA tools like NVML or DCGM measure utilization. gpu metric, they divide time into small slices—typically milliseconds. For each time slice, they check only whether at least one CUDA kernel is resident on any of the GPU's cores, called Streaming Multiprocessors (SMs). It doesn't matter how much actual work the GPU is doing—whether it’s ready to execute or already executing—just being "occupied" counts as 100% utilization during that moment. 100% utilization from the utilization. gpu metric doesn't reflect: Functional unit activity – It doesn’t show whether FP32 units, Tensor Cores, or memory controllers are actively working or sitting idle. SM occupancy – It ignores how fully the SMs are used. An SM may be active but running only a small number of warps (e. g. , just 1 out of many possible). Voltage/frequency state – It doesn't account for power-saving features like DVFS (Dynamic Voltage and Frequency Scaling) or clock-gating, where parts of the chip may run slower or be temporarily turned off. Example cases where "100% Util" masks variable heat output The utilization. gpu metric often shows 100%, but this can be misleading. The table below compares what the metric reports with the GPU’s actual activity and power usage, and clarifies what that 100% utilization really means in different scenarios. Case What the Metric Shows (utilization. gpu) What the GPU Actually Doing (Silicon Activity) Resulting Power / Heat What It Really Means Compute-bound GEMM (FP16/FP8 tensor cores) 100% GPU util when kernel... --- > Go beyond Google's AI for data center cooling—ProphetStor combines AI-driven resource management with smart liquid cooling to cut waste, boost performance, and meet ESG goals. - Published: 2025-03-12 - Modified: 2025-06-11 - URL: https://prophetstor.com/white-papers/ai-driven-data-center-cooling-google-vs-prophetstor/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Introduction Data centers today face unprecedented challenges from rapidly escalating computing demands, especially those driven by artificial intelligence (AI) and high-performance computing (HPC). These advanced workloads result in substantially higher power densities, significantly increasing operational costs and environmental impacts due to cooling inefficiencies. With data center energy consumption expected to reach approximately 2% of global electricity usage by 2025 and up to 21% globally by 2030 (AI models are devouring energy. Tools to reduce consumption are here, if data centers will adopt | Lincoln Laboratory), the adoption of advanced cooling technologies for AI data centers is no longer optional—it's essential. Google's AI-Enabled Cooling approach, pioneered in collaboration with DeepMind, demonstrates significant improvements by leveraging sophisticated AI algorithms to optimize traditional air-based cooling systems autonomously. ProphetStor's Smart Liquid Cooling advances this concept further by integrating AI-driven, application-aware resource management directly with advanced cooling technologies, such as direct liquid cooling (DLC). The transition from air cooling to liquid cooling is a necessary prerequisite to the adoption of the latest energy-hungry GPU models, like the NVIDIA GB200. ProphetStor is helping to maximize the benefits of liquid cooling by providing a Smart Liquid Cooling software platform that orchestrates liquid cooling across GPU clusters to lower PUE, increase fault tolerance, boost performance, lengthen GPU lifespans, and improve ESG reporting, while driving API standardization. This whitepaper presents a detailed comparative analysis of Google's air-cooling methodology with ProphetStor's liquid cooling methodology, examining technical distinctions including application awareness, energy efficiency, and deployment complexity, as well as respective... --- > Federator.ai GPU Booster optimizes GPU resource allocation for LLM training workloads across Kubernetes platforms like Red Hat OpenShift, SUSE Rancher, and VMware Tanzu. - Published: 2024-10-08 - Modified: 2024-10-09 - URL: https://prophetstor.com/gpu-operations-on-kubernetes/ Training AI, ML, and Large Language Models (LLMs) poses significant challenges due to their resource-intensive and unpredictable demands. These workloads often lead to resource imbalances, higher costs, and scalability issues, especially in large-scale GPU clusters where utilization is hard to optimize. The dynamic nature of training complicates resource forecasting, leading to either underused infrastructure or performance bottlenecks. To address these challenges, Federator. ai GPU Booster utilizes patented AI-powered algorithms to capture the nuances of training workload patterns and optimize GPU resource allocation across clusters. It intelligently balances resources based on real-time demand and performs seamless pod migrations within Kubernetes environments to ensure minimal downtime and optimal efficiency. By supporting various Kubernetes platforms, Federator. ai GPU Booster provides a robust, application-aware solution that streamlines AI training operations, reduces costs, and maximizes GPU utilization across diverse infrastructures. Full-Stack Visibility and Optimization Tap into metadata and operational metrics from GPU hardware, the Kubernetes platforms, operators, AI/ML libraries, and frameworks to comprehensively view resource allocation and consumption, enabling informed resource optimization. Hyper-Efficient Training Throughput Agilely dispatch resources to support parallel MultiTenant AI/ML training and seamlessly migrate containerized applications in Kubernetes systems, avoiding performance disruption while significantly reducing training time and maximizing GPU utilization. AI/ML Workload Pattern-Aware Insights Leverage patented Spatial and Temporal GPU Optimization to multidimensionally predict resource needs for parallel AI/ML jobs, and use Cascade Causal Analysis to identify resource correlations for optimal, application-aware allocation. ESG Compliance for Sustainability Capture resource demands from bursty AI training traffic to efficiently allocate GPU resources for... --- > Federator.ai optimizes IT/Cloud resource allocation for IT operations across Kubernetes clusters on EKS, AKS, GKE, Red Hat OpenShift, and SUSE Rancher. - Published: 2024-10-08 - Modified: 2024-10-15 - URL: https://prophetstor.com/it-cloud-operations-on-kubernetes/ Container adoption enhances operational agility and speeds up application deployment. However, it also introduces substantial overhead when managing compute resources across complex setups like on-premises, hybrid cloud, MultiCloud, and edge environments. The varying resource demands of these environments can lead to inefficient allocation, higher costs, and inconsistent performance, making it difficult for organizations to fully realize the benefits of containerization at scale. To address these challenges, Federator. ai offers an AI-powered solution that optimizes container resources across Kubernetes platforms. Using advanced machine learning algorithms, it dynamically analyzes workloads, predicts resource needs, and adjusts allocations in real time for efficient utilization and minimal waste. This approach simplifies container management in multi-environment deployments, reduces operational costs, and boosts performance. Its platform-agnostic design ensures optimal container performance in a single cluster or across MultiCloud and edge locations, making it a versatile tool for managing complex container ecosystems. Previous Next Multi-layer Visibility and OptimizationLeverage collected metadata and operational metrics from multi-layer infrastructure operations to provide ongoing, Just-in-Time Fitted recommendations for optimized resource orchestration using AI-powered workload predictions. Resource Utilization and Cost ImprovementAuto-scale container resources based on real-time application demands. Identify workload patterns and recommend the most cost-effective portfolio of instance types and quantities, enhancing resource utilization, eliminating over-provisioning, and supporting sustainability. Performance Assurance and ResilienceUse Federator. ai’s patented Cascade Causal Analysis to identify resource correlations among hardware, cloud resources, Kubernetes layers, and applications. This enables efficient allocation of resources to mission-critical applications while minimizing resource usage. Policy-compliant AutomationAutomate continuous operation optimization by accurately interpreting... --- > Federator.ai optimizes IT/Cloud resource allocation for IT operations across VM clusters on VMware vSphere, AWS EC2, Azure, and Google. - Published: 2024-10-08 - Modified: 2024-10-09 - URL: https://prophetstor.com/it-cloud-operations-on-virtual-machine-vm/ Managing large-scale VM deployments across platforms like Amazon EC2, Azure, Google Compute Engine, and VMware vSphere can be complex. Each environment has unique configurations, leading to inefficiencies, high costs, and performance issues from misconfigurations and over-provisioning. In hybrid and multi-cloud setups, these challenges are even greater, complicating consistent resource utilization and cost management. To address these issues, Federator. ai offers an AI-powered solution that provides intelligent, application-aware optimization across these environments. By leveraging machine learning to analyze workload patterns and adjust resource allocations in real-time, it ensures optimal performance and cost efficiency. This approach helps prevent over-provisioning and underutilization, making it ideal for managing diverse VM infrastructures with minimal manual intervention. Previous Next Visibility and Optimization of VM ResourcesLeverage collected metadata and operational metrics to gain real-time visibility into VM resource usage with Federator. ai. Quickly identify opportunities for optimizing clusters and nodes, enabling accurate provisioning to ensure operational resilience. Cost ImprovementOptimize infrastructure utilization with Federator. ai by providing accurate capacity projections and recommending optimal instance types and quantities. Assess the TCO of on-premises components, enabling executives to evaluate long-term costs and make cost-effective decisions. Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you Read More Optimizing VMware with Federator. ai: Boosting Efficiency, Performance, and Cost Savings in Virtual Infrastructure Whitepaper Introduction to ProphetStor’s Federator. ai: Cloud Operations, Optimized Whitepaper --- > Federator.ai GPU Booster offers visibility into environmental metrics and will soon add air and liquid cooling metrics to ensure uninterrupted training and support ESG goals. - Published: 2024-09-20 - Modified: 2025-05-28 - URL: https://prophetstor.com/esg-alignment-and-smart-cooling/ With AI clusters driving rack power beyond 130 kW and stricter ESG mandates emerging across the globe, data center operators are under pressure to reduce their environmental footprint while scaling AI workloads efficiently. Federator. ai Smart Liquid Cooling transforms conventional static cooling into an intelligent, predictive system that dynamically aligns cooling effort with actual GPU heat output. By reducing pump and chiller energy without compromising thermal safety, it empowers organizations to cut energy waste, improve system longevity, and meet ESG goals—while supporting the demands of next-gen AGI training. Visibility into Cooling and Environmental Metrics Provide detailed monitoring of power usage, coolant flow, GPU temperatures, and ΔT across racks and clusters. This visibility helps data centers quantify energy savings, track cooling performance, and avoid thermal over-provisioning. Predictive Cooling Control for Energy ReductionUse workload-aware AI forecasting to adjust pump speeds and valve positions in real time, reducing cooling energy by up to 30% during low-load phases while keeping junction temperatures under throttle limits. Sustainability Without Compromise Align cooling operations with workload intent—not just static design flow rates—ensuring ESG compliance and long-term environmental sustainability without sacrificing compute throughput or rack density. Read More AI-Driven Data Center Cooling: Google vs. ProphetStor Whitepaper Key Insight: “100% GPU Util” ≠ “100% Heat” Whitepaper Proving Why 1. 25-1. 60 L min⁻¹ kW⁻¹ Is a Good Design Rule but Wasteful Without Variable-Speed Control Whitepaper --- > Federator.ai Stack enables quick setup of Federator.ai GPU Booster with essential AI software components for AI/ML training, from platforms to driver downloads. - Published: 2024-09-05 - Modified: 2025-05-26 - URL: https://prophetstor.com/quick-adoption-in-ai-ecosystem/ For a quick time-to-value when adopting Federator. ai GPU Booster, we offer a one-step installation and managed upgrade path with the Federator. ai Stack. Following simple installation instructions, you can quickly set up an ecosystem with all the essential AI software ready for productive AI/ML training. Quick Time-to-Value Adoption Provide a simple installation process to ensure Federator. ai GPU Booster, along with the necessary AI training components—from platforms to driver downloads—are ready for AI/ML training. Automatic Detection of Required SoftwareAutomatically detect and update AI toolkits to build a comprehensive AI training environment, eliminating cumbersome and error-prone manual checks. One-Step Installation Offer a step-by-step Federator. ai Stack installation video to guide a streamlined setup of the AI/ML training ecosystem, ensuring all necessary components are included. Diagram∣Federator. ai Stack installation process Video | Federator. ai Stack optimizes the Time-to-Online of GPU servers https://youtu. be/PXMfOGB4KEo Read More Maximize GPU Efficiency in MultiTenant LLM Training: Federator. ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization Whitepaper Optimizing AI: The Critical Role of Dynamic GPU Resource Allocation in Large Language Model Training Whitepaper AI-Defined Data Center: Federator. ai DataCenter OS for Optimal Efficiency, Sustainability, Automation, and Global Compute Platform Integration Whitepaper --- > Federator.ai GPU Booster forecasts GPU needs for AI/ML workloads, reducing execution time by up to 50%, optimizing resources, and preventing training interruptions. - Published: 2024-09-05 - Modified: 2025-05-26 - URL: https://prophetstor.com/ai-ml-throughput-enhancement/ Volatile GPU demand from AI/ML workloads makes resource consumption difficult to predict, leading to interruptions in training when resources for parallel training are unavailable, as well as increased spending on costly GPU server expansions. Federator. ai GPU Booster analyzes metadata and operational metrics to gain insights into each individual AI/ML workload pattern and accurately forecast the dynamic GPU resource requirements for each training session, thereby reducing the total execution time by up to 50% and speeding up e/acc-aligned AI advancement. Visibility of Workload Overview and Detail Provide visibility with line charts of different AI/ML workloads across clusters over time, and track each workload’s status (running, pending, failed, succeeded) along with its resource requirements down to the pod level. Predictions of Each Workload for Resource OptimizationTap into machine learning algorithms to provide resource allocation recommendations, enabling trainers to adjust between epochs so that the new resource configuration closely aligns with workload trends. Optimal Resource Allocation for MultiTenant AI Training Jobs Considering the fluctuation of each workload from an accumulated resource requirements perspective is crucial to ensuring sufficient resources for uninterrupted MultiTenant AI/ML/LLM training jobs. Read More Maximize GPU Efficiency in MultiTenant LLM Training: Federator. ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization Whitepaper Optimizing AI: The Critical Role of Dynamic GPU Resource Allocation in Large Language Model Training Whitepaper AI-Defined Data Center: Federator. ai DataCenter OS for Optimal Efficiency, Sustainability, Automation, and Global Compute Platform Integration Whitepaper --- > Federator.ai GPU Booster optimizes NVIDIA MIG technology, enhancing GPU utilization by up to 90% with detailed metrics and configuration recommendations. - Published: 2024-09-05 - Modified: 2025-06-19 - URL: https://prophetstor.com/gpu-utilization-optimization/ GPU servers are extremely expensive, especially those with high-end NVIDIA GPUs like the A100, H100/H200, and GB100. To make AI/ML training more efficient, these resources should be fully utilized to their maximum potential. Federator. ai GPU Booster integrates with NVIDIA’s high-end GPUs using Multi-Instance GPU (MIG) technology, which partitions a GPU into smaller instances with completely isolated memory and compute cores. This capability to manage both physical and logical GPUs enables Federator. ai GPU Booster to enhance GPU utilization with the most resource-efficient MIG instance configurations for the GPU cluster by up to 90%. Visibility for Efficient GPU Resource Configuration View both physical GPUs with detailed utilization and memory metrics, along with logical GPUs in various configurations. Track each type of logical GPU requested to ensure they are ready for allocation to different workloads. High Quality of Service for MultiTenant AI Training Leverage MIG to provide high QoS due to the isolation of resources for each GPU instance, effectively eliminating resource interference or competition among AI applications. Recommendations for Efficient GPU Resource Configuration Provide detailed configuration recommendations for each GPU server to efficiently accommodate dynamic workloads and significantly enhance overall utilization. Read More Maximize GPU Efficiency in MultiTenant LLM Training: Federator. ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization Whitepaper Optimizing AI: The Critical Role of Dynamic GPU Resource Allocation in Large Language Model Training Whitepaper AI-Defined Data Center: Federator. ai DataCenter OS for Optimal Efficiency, Sustainability, Automation, and Global Compute Platform... --- > Federator.ai GPU Booster uses Prometheus for secure, agentless metrics collection, optimizing GPU resource planning for dynamic LLM training. - Published: 2024-09-03 - Modified: 2024-09-04 - URL: https://prophetstor.com/fgb-integrations/prometheus/ Federator. ai GPU Booster® & Prometheus Integration Prometheus, a 100% open-source and community-driven system, is used for systems and service monitoring. It collects metadata and operational metrics from configured targets at specified intervals, evaluates rule expressions, displays the results, and can trigger alerts when certain conditions are met. With Prometheus integration, Federator. ai GPU Booster analyzes dynamic workload patterns and provides predictions for resource consumption and recommendations for resource configurations. Users can easily manage clusters and AI/ML training from the Federator. ai GPU Booster web console. Diagram∣Federator. ai GPU Booster and Prometheus integration workflow Video∣The features and the GUI (graphical user interface) of Federator. ai GPU Boosterhttps://youtu. be/6HDnTIujHkERequest a demo today and harness the power of machine learning for your Prometheus monitoring environments. --- > Key roles in product management, strategic partnerships, and business development at IBM, EMC, and Dell. Leadership in startups focused on data analytics, AI, and renewable energy management. - Published: 2024-08-01 - Modified: 2024-08-01 - URL: https://prophetstor.com/team/anton-prenneis/ Anton Prenneis Linkedin-in VP of Business Development, North America Before joining ProphetStor, Anton Prenneis built a distinguished career in enterprise software, beginning as a software engineer at IBM. At IBM, he developed robotic tools for mainframe manufacturing and wrote system software for the SP supercomputer family. He then transitioned into various business-focused roles in product management, competitive intelligence, software licensing, strategic partnerships, marketing, and business development at IBM Software Group, EMC Corporation, and Dell Technologies. Most recently, Anton held leadership positions at Cardinality Ltd. and AutoGrid Systems, two pioneering startups with SaaS platforms leveraging data analytics and AI. At Cardinality Ltd. , he focused on mobile telecommunications use cases, while at AutoGrid Systems, he specialized in the flexible management of distributed renewable energy resources. Anton brings to ProphetStor a unique combination of technical expertise and strategic business insights. His mission is to drive the growth of ProphetStor in North America by advancing GPU optimization and efficient data center energy management. Anton holds an M. S. in Computer Science from Rensselaer Polytechnic Institute and an MBA from Columbia Business School. He is enthusiastic about contributing to ProphetStor's innovative efforts and helping the company achieve its vision. Meet Our Team --- > Discover how Federator.ai DataCenter OS manages AI-driven data centers by virtualizing, visualizing, automating, and globalizing compute resources for efficient and proactive environmental management. - Published: 2024-07-08 - Modified: 2025-03-14 - URL: https://prophetstor.com/white-papers/federator-ai-datacenter-os-for-addc/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon I. Executive Summary AI technologies have significantly transformed various sectors, leading to unprecedented demands on data centers. Traditional data centers, however, are grappling with the increasing complexity and substantial energy requirements of AI workloads. This necessitates a shift in the conventional wisdom of data center management, especially considering factors such as electricity, cooling, and overall operational efficiency. Current Challenges and Issues Increasing Demand for AI Data Centers: As highlighted in the comprehensive analysis "Situational Awareness: The Decade Ahead" by Leopold Aschenbrenner, the rapid progression towards Artificial General Intelligence (AGI) and subsequent superintelligence necessitates a substantial upgrade in data center infrastructure. The shift from $10 billion to potentially trillion-dollar clusters within a decade underscores the exponential growth in computational demands. This transition involves significant investments in GPU clusters, data centers, and the associated power infrastructure, which is predicted to see trillions of dollars in investments by the end of the decade. Energy and Cooling Requirements: Traditional data centers consume vast amounts of electricity and face challenges in cooling efficiency, particularly as AI workloads intensify. The 'Electricity 2024' report underscores the need for innovative solutions to manage the dramatic increases in power consumption projected for the near future. This analysis suggests that merely relying on existing energy solutions will be insufficient to meet the escalating demands, highlighting the importance of creativity and out-of-the-box thinking in energy sourcing and cooling methodologies. Efficiency and Sustainability: Managing data centers efficiently while adhering to sustainability goals is becoming increasingly complex. However, the proposed paradigm shift... --- > Please fill out the form to the right to request a demo, and also check out our feature demo video and whitepapers for more information. We will contact you soon to schedule your demo. - Published: 2024-06-26 - Modified: 2024-07-04 - URL: https://prophetstor.com/request-demo-of-fgb/ Request a demo of Federator. ai GPU Booster Please fill out the form to the right to request a demo, and also check out our feature demo video and whitepapers for more information. We will contact you soon to schedule your demo. Feature Demo Video Optimizing AI: The Critical Role of Dynamic GPU Resource Allocation in Large Language Model Training Whitepaper Maximize GPU Efficiency in MultiTenant LLM Training: Federator. ai GPU Booster on High-End GPU Servers Cuts Job Times by 50% and Doubles GPU Utilization Whitepaper --- - Published: 2024-05-30 - Modified: 2024-06-26 - URL: https://prophetstor.com/fgb-demo-request-submitted/ Your demo request for Federator. ai GPU Booster has been sent. Thank you for your interest in Federator. ai GPU Booster. Before our team contacts you with further information, we suggest visiting our FAQ page or Whitepapers. These resources will provide a quick overview of the benefits of Federator. ai GPU Booster and help you understand how its features can address the critical issues you are facing. FAQ Demo Videos Whitepapers Home --- > The Federator.ai Stack offers a comprehensive ecosystem that connects hardware, like GPU servers, with software, such as LLM applications, enabling the Federator.ai GPU Booster to run. - Published: 2024-05-21 - Modified: 2025-06-02 - URL: https://prophetstor.com/federator-ai-gpu-booster/federator-ai-stack/ One-Step Installation with Required AI Software The Federator. ai Stack features a comprehensive suite of tools that provides everything necessary for productive AI/ML training. Its seamless one-step installation process bypasses cumbersome, error-prone parts, ensuring a well-set-up environment with essential AI software readily accessible. Designed for researchers, data scientists, and IT professionals, it simplifies the deployment and management of AI applications, allowing you to concentrate on AI innovations while we manage the complexities of infrastructure optimization. Follow the installation process, and all necessary software will be automatically detected and installed if absent, even on a bare metal GPU server. The Federator. ai Stack ensures a quick time-to-value adoption, enabling the Federator. ai GPU Booster to work right out of the box. The Benefits of the Federator. ai Stack The Federator. ai Stack streamlines the setup of necessary AI training components, from platforms to drivers, and automatically installs essential software on GPU servers. This ensures quick adoption of the powerful Federator. ai GPU Booster. A Comprehensive Toolkit Stack Ready for installation The Federator. ai Stack is expertly designed to meet the various needs of GPU servers armed with top-tier Nvidia GPUs, such as the A100, H100, and GB200, whether they operate with a base OS or not. By following the instructions in the Federator. ai Stack guide, you can enjoy a silky-smooth installation process with all essential AI training software. This ensures you quickly gain the benefits that the Federator. ai GPU Booster offers. Video | Federator. ai Stack optimizes the Time-to-Online... --- > Discover how our technology and Kubernetes enhance efficiency, reduce costs, and promote sustainability through dynamic GPU resource allocation for AI and LLM training. - Published: 2024-05-17 - Modified: 2025-05-28 - URL: https://prophetstor.com/white-papers/optimized-dynamic-gpu-allocation-in-llm-training/ - 頁面分類: Whitepapers - Folder: Whitepapers Executive Summary The Importance of GPU Resource Management in LLM Training In the rapidly evolving field of artificial intelligence, training Large Language Models (LLMs) is one of the most resource-intensive tasks. These models, fundamental to advancements in AI applications like natural language processing, require significant computational power, primarily provided by Graphics Processing Units (GPUs). Efficient GPU resource management is crucial for optimizing the training process and managing operational costs effectively. The ability to dynamically allocate and utilize these resources can significantly impact the speed and efficiency of model training, directly influencing the practical deployment and scalability of AI technologies. Advantages of Dynamic Over Static Resource Allocation Dynamic resource allocation offers substantial advantages over traditional static methods when managing the heavy and variable demands of GPU resources necessary for LLM training. Unlike static allocation, which assigns fixed resources regardless of actual usage, dynamic allocation adjusts resources in real time based on workload demands. This adaptability prevents resource wastage and ensures computational power is available precisely when needed, leading to faster training times and lower costs. Dynamic systems can respond to changes in demand instantly, enhancing efficiency and allowing AI developers to leverage computational resources more strategically. Key Findings and Technological Solutions Discussed The whitepaper discusses several vital findings and technological solutions that facilitate effective GPU resource management:Technological Solutions: Technologies like Kubernetes and Federator. ai GPU Booster are pivotal in enabling dynamic resource allocation. Kubernetes manages and scales containerized applications efficiently, while Federator. ai GPU Booster enhances these capabilities by predicting resource... --- > Enhance AI/ML training efficiency, optimize Kubernetes resources, boost total throughput, and reduce emissions in MultiTenant environments. - Published: 2024-03-05 - Modified: 2025-05-26 - URL: https://prophetstor.com/federator-ai-gpu-booster/ Overview Federator. ai GPU Booster leverages advanced multi-layer correlation and machine learning technologies on Kubernetes to address the challenges of managing GPU resources in competitive AI and ML environments. Designed for MultiTenant settings, it efficiently orchestrates AI/ML workloads, particularly in large language model training. By dynamically adjusting GPU allocations to accommodate the varying demands of AI training workloads, Federator. ai GPU Booster optimizes resource usage and enhances training efficiency, enabling organizations to fully harness their AI/ML capabilities, thereby accelerating progress in the field in alignment with e/acc principles. Advanced Technologies Behind Predictive Analytics and Dynamic GPU Resource Allocation Employ predictive analytics to accurately forecast AI/ML workloads, enabling well-informed GPU allocation that guarantees optimal computational power for each project. Multi-Instance GPU (MIG) Utilization on Kubernetes Utilize Multi-Instance GPU (MIG) technology on Kubernetes to partition a single GPU into multiple instances, providing isolation and parallelism tailored for AI/ML workloads. Adaptability to Diverse AI/ML Workloads Dynamically Optimize GPU allocations to cater to a wide range of for AI/ML workloads, enhancing efficiency and minimizing resource wastage in complex, MultiTenant environments. Benefits of Federator. ai GPU Booster Minimize Latency Avoid resource competition during AI/ ML training and balance peaks and troughs of workloads by recognizing patterns in each training session. Efficient Resource Allocation Leverage Multi-Instance GPU (MIG) technology to run MultiTenant training sessions in parallel, efficiently allocating the necessary resources based on ML algorithms. Maximize Total Throughput Fully utilize current GPUs by strategically reallocating resources among concurrent training sessions, significantly enhancing overall training throughput. ESG/... --- > Discover how Federator.ai GPU Booster revolutionizes GPU optimization on high-end servers, slashing LLM training job times by 50% and doubling GPU utilization. - Published: 2024-01-04 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/maximizing-gpu-efficiency-in-multitenant-llm-training/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Executive Summary In the dynamic world of AI and machine learning, efficient management of GPU resources in MultiTenant environments is paramount, particularly for Large Language Model (LLM) training. This whitepaper focuses on the pivotal role of ProphetStor's Federator. ai GPU Booster in transforming GPU resource management for LLM training workloads on large GPU servers equipped with NVIDIA H100s. Challenges in GPU Resource Management Dynamic and Diverse AI/ML Workloads: The varying demands of AI/ML tasks, particularly in LLM training, necessitate an agile and efficient approach to GPU resource allocation, often hampered by static methods leading to underutilization. MultiTenant Environment Complexities: The shared nature of GPU resources in Kubernetes cloud environments requires sophisticated management to prevent resource contention and ensure optimal utilization. Federator. ai GPU Booster: A Game-Changer in GPU Management Precision in Predictive Resource Allocation: Federator. ai GPU Booster's advanced predictive analytics enable exact forecasting of GPU resource needs for various AI/ML jobs, ensuring maximum system efficiency. Seamless Kubernetes Integration: Federator. ai GPU Booster's integration with Kubernetes allows dynamic, automatic GPU resource distribution, essential for high-performing AI/ML workloads. Enhanced GPU Utilization with Federator. ai GPU Booster: Federator. ai GPU Booster’s GPU Management and Optimization ensures an increase in GPU resources utilization efficiency, significantly benefiting intensive tasks like LLM training. Adaptive Resource Management: In MultiTenant scenarios, Federator. ai GPU Booster's capability to recommend and adjust GPU resources ensures fair and efficient distribution, maintaining system balance. Quantifiable Gains: Implementing Federator. ai GPU Booster's guidance results in on average 50% reduction in job... --- > Federator.ai optimizes operations on Azure Cloud with AI for performance and cost efficiency, tackling misconfiguration and over-provisioning. - Published: 2023-08-10 - Modified: 2024-09-04 - URL: https://prophetstor.com/azure-virtual-machine/ Virtual machines in Azure Azure virtual machines are a type of on-demand, scalable computing resources offered by Microsoft Azure. They provide the flexibility of virtualization without the need to purchase or maintain the physical hardware that supports it. Azure virtual machines offer a quick and convenient solution for development and testing, running applications in the cloud, or extending your data center with network connectivity. Benefits of Federator. ai employed for Optimization of Google Compute Engine Managing a large VM deployment in Azure can be a challenging task. Performance and cost issues can arise due to misconfiguration, over-provisioning, and other factors. To address these challenges, Federator. ai provides an AI-powered solution for adding application-aware optimization to Azure virtual machines. Diagram: Federator. ai and Azure virtual machine work together to configuring new VM clusters Visibility and Optimization of VM ResourcesLeverage collected metadata and operational metrics to gain real-time visibility into VM resource usage with Federator. ai. Quickly identify opportunities for optimizing clusters and nodes, enabling accurate provisioning to ensure operational resilience. Cost ImprovementOptimize infrastructure utilization with Federator. ai by providing accurate capacity projections and recommending optimal instance types and quantities. Assess the TCO of on-premises components, enabling executives to evaluate long-term costs and make cost-effective decisions. Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai utilizes metrics from Azure Monitor to implement ML-based workload predictions and resource recommendations for VM clusters on Google Cloud. - Published: 2023-08-10 - Modified: 2023-08-14 - URL: https://prophetstor.com/integrations/federator-ai-microsoft-azure-monitor-integration/ Federator. ai® & Microsoft Azure Monitor Integration Azure Monitor is a monitoring solution for collecting, analyzing, and responding to monitoring data from cloud and on-premises environments. The data from resources running on the Azure Cloud can be collected and tracked in real time, allowing Federator. ai to monitor these operational metrics and continuously provide machine learning-based workload predictions and resource recommendations for VM clusters. A single installation of Federator. ai enables the management of multiple clusters, freeing up administrators and enhancing cost-effectiveness and performance in IT operations. Diagram∣The Federator. ai/ Azure Monitor integration workflow Video∣The features and the GUI (graphical user interface) of Federator. aihttps://youtu. be/AeSH8yGGA3Q Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai optimizes operations on Google Cloud with AI for performance and cost efficiency, tackling misconfiguration and over-provisioning. - Published: 2023-06-26 - Modified: 2024-09-04 - URL: https://prophetstor.com/google-compute-engine/ GCE for VMsGoogle Compute Engine (GCE) is an Infrastructure as a Service (IaaS) offering that allows clients to create applications and run workloads on Google's physical hardware. GCE provides a scalable number of virtual machines (VMs) to serve as large compute clusters on Google Cloud’s global infrastructure. It supports cloud storage, customized VMs, load balancing, and different instance options. Benefits of Federator. ai employed for Optimization of Google Compute EngineManaging a large VM deployment on GCE can be a challenging task. Performance and cost issues can arise due to misconfiguration, over-provisioning, and other factors. To address these challenges, Federator. ai provides an AI-powered solution for effectively adding application-aware optimization to GCE. Diagram: Federator. ai and Google Cloud’s operations suite work together to configuring new VM clusters Visibility and Optimization of VM ResourcesLeverage collected metadata and operational metrics to gain real-time visibility into VM resource usage with Federator. ai. Quickly identify opportunities for optimizing clusters and nodes, enabling accurate provisioning to ensure operational resilience. Cost ImprovementOptimize infrastructure utilization with Federator. ai by providing accurate capacity projections and recommending optimal instance types and quantities. Assess the TCO of on-premises components, enabling executives to evaluate long-term costs and make cost-effective decisions. Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai utilizes metrics from Google Cloud operetions suite to implement ML-based workload predictions and resource recommendations for VM clusters on Google Cloud. - Published: 2023-06-21 - Modified: 2023-08-14 - URL: https://prophetstor.com/integrations/federator-ai-google-clouds-operations-suite-integration/ Federator. ai® & Google Cloud’s operations suite Integration Google Cloud operations suite (formerly Stackdriver) is a platform for monitoring, troubleshooting, and improving application performance in the Google Cloud environment. The data from resources running on Google Cloud can be collected and tracked in real time, allowing Federator. ai to monitor these operational metrics and continuously provide machine learning-based workload predictions and resource recommendations for VM clusters. A single installation of Federator. ai enables the management of multiple clusters, freeing up administrators and enhancing cost-effectiveness and performance in IT operations. Diagram∣The Federator. ai/ Google Cloud operations suite integration workflow Video∣The features and the GUI (graphical user interface) of Federator. aihttps://youtu. be/AeSH8yGGA3Q Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai utilizes metrics from Amazon CloudWatch to implement machine learning-based workload predictions and resource recommendations for VM clusters on AWS EC2. - Published: 2023-06-19 - Modified: 2023-08-14 - URL: https://prophetstor.com/integrations/federator-ai-amazon-cloudwatch-integration/ - Folder: Integrations Federator. ai® & Amazon CloudWatch Integration Amazon CloudWatch is a monitoring service that provides data for Amazon Web Services (AWS) infrastructure resources. The data from resources running on the AWS EC2 platform can be collected and tracked in real time, allowing Federator. ai to monitor these operational metrics and continuously provide machine learning-based workload predictions and resource recommendations for VM clusters. A single installation of Federator. ai enables the management of multiple clusters, freeing up administrators and enhancing cost-effectiveness and performance in IT operations. Diagram∣The Federator. ai/Amazon CloudWatch integration workflow Video∣The features and the GUI (graphical user interface) of Federator. aihttps://youtu. be/AeSH8yGGA3Q Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai utilizes metrics from vCenter to implement machine learning-based workload predictions and resource recommendations for VM clusters on VMware vSphere. - Published: 2023-06-19 - Modified: 2023-08-14 - URL: https://prophetstor.com/integrations/federator-ai-vmware-vcenter-integration/ Federator. ai® & VMware vCenter Integration VMware vCenter is a server management software that provides a centralized platform for controlling vSphere environments for visibility across hybrid clouds. By integration with vCenter, one of the data sources in VM environments, Federator. ai can monitor and track operational metrics and continuously provide machine learning-based workload predictions and resource recommendations for VM clusters. A single installation of Federator. ai enables the management of multiple clusters, both locally and remotely, freeing up administrators and enhancing cost-effectiveness and performance in IT operations. Diagram∣The Federator. ai/VMware vCenter integration workflow Video∣The features and the GUI (graphical user interface) of Federator. aihttps://youtu. be/AeSH8yGGA3Q Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai enhances cost control, security config, and interoperability with a comprehensive view across platforms, enabling intelligent resource allocation and automation. - Published: 2023-06-02 - Modified: 2025-06-05 - URL: https://prophetstor.com/white-papers/taming-multicloud-chaos/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Introduction The digital landscape is evolving at an unprecedented pace, and MultiCloud solutions are at the forefront of this transformation. To streamline operations and drive innovation, enterprises are increasingly adopting a combination of cloud environments and providers. However, this variety of cloud resources introduces a new set of challenges. As Mike Bechtel, managing director and chief futurist at Deloitte Consulting LLP, explains in his article "Above the Clouds: Taming MultiCloud Chaos," these challenges include managing heterogeneous platforms, services, and interfaces while fully harnessing the benefits of cloud investments—such as on-demand self-service, broad network access, rapid elasticity, resource pooling, and measured service. To navigate this complex landscape, businesses need solutions that simplify MultiCloud management and unlock the full potential of their cloud investments. This is where ProphetStor and its flagship product, Federator. ai, come into play. ProphetStor, a pioneer in AI-powered data and cloud services, developed Federator. ai specifically to address the complexities of MultiCloud operations. Federator. ai adds a layer of abstraction and automation to MultiCloud management, enabling businesses to optimize their cloud resources, reduce costs, enhance security, and boost operational efficiency. The MultiCloud Challenges Adopting a MultiCloud strategy provides flexibility in resource deployment, reduces the risk of vendor lock-in, and helps mitigate unexpected outages. According to the Flexera 2024 State of the Cloud Report, nearly 90% of businesses now use MultiCloud environments, leveraging a combination of private, public, and hybrid clouds. However, despite its advantages, MultiCloud also presents challenges. One of the biggest is cost control. Managing multiple... --- - Published: 2023-05-23 - Modified: 2024-09-04 - URL: https://prophetstor.com/vmware-tanzu/ Popular Kubernetes Platform for VMsVMware Tanzu is a platform that enables organizations to build and run modern applications using Kubernetes. Tanzu provides a consistent, secure, and scalable environment for containers and microservices, making it easier to accelerate application development and delivery. Benefits of Federator. ai employed for Optimization of VMware TanzuManaging a large Tanzu deployment can be challenging, especially when it comes to performance and cost optimization. To address this, Federator. ai provides an AI-powered solution for adding application-aware optimization to Tanzu. Diagram: Application-aware optimization using Federator. ai in VMware Tanzu setups Multi-layer Visibility and OptimizationLeverage collected metadata and operational metrics from multi-layer infrastructure operations to provide ongoing, Just-in-Time Fitted recommendations for optimized resource orchestration using AI-powered workload predictions. Resource Utilization and Cost ImprovementAuto-scale container resources based on real-time application demands. Identify workload patterns and recommend the most cost-effective portfolio of instance types and quantities, enhancing resource utilization, eliminating over-provisioning, and supporting sustainability. Performance Assurance and ResilienceUse Federator. ai’s patented Cascade Causal Analysis to identify resource correlations among hardware, cloud resources, Kubernetes layers, and applications. This enables efficient allocation of resources to mission-critical applications while minimizing resource usage. Policy-compliant AutomationAutomate continuous operation optimization by accurately interpreting metadata and predicting workloads, then automatically recommending optimal resources. Users can also access Federator. ai’s orchestration script to ensure compliance with company policies. Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you Read More Whitepaper｜Adding Application-Aware Optimization to VMware Tanzu Using ProphetStor Federator.... --- - Published: 2023-05-22 - Modified: 2024-09-04 - URL: https://prophetstor.com/red-hat-openshift-suse-rancher/ Popular Kubernetes Platforms Red Hat OpenShift and SUSE Rancher are two of the most popular enterprise-grade Kubernetes platforms used to build, deploy, and manage containerized applications. Both OpenShift and Rancher offer advanced features such as automated scaling, rolling updates, and integrated security to streamline application deployment and management. Benefits of Federator. ai employed for Optimization of Kubernetes Platforms Container adoption can introduce operation agility but also significant operational overhead, especially when managing compute resources across on-premises, hybrid cloud, MultiCloud, or edge architectures. To address this challenge, Federator. ai offers an AI-powered solution that optimizes container resources on top of VMs or bare metal in OpenShift and Rancher platforms. Diagram: Federator. ai takes the monitored data and provides the operation recommendations for different layers Multi-layer Visibility and OptimizationLeverage collected metadata and operational metrics from multi-layer infrastructure operations to provide ongoing, Just-in-Time Fitted recommendations for optimized resource orchestration using AI-powered workload predictions. Resource Utilization and Cost ImprovementAuto-scale container resources based on real-time application demands. Identify workload patterns and recommend the most cost-effective portfolio of instance types and quantities, enhancing resource utilization, eliminating over-provisioning, and supporting sustainability. Performance Assurance and ResilienceUse Federator. ai’s patented Cascade Causal Analysis to identify resource correlations among hardware, cloud resources, Kubernetes layers, and applications. This enables efficient allocation of resources to mission-critical applications while minimizing resource usage. Policy-compliant AutomationAutomate continuous operation optimization by accurately interpreting metadata and predicting workloads, then automatically recommending optimal resources. Users can also access Federator. ai’s orchestration script to ensure compliance with company policies.... --- - Published: 2023-05-22 - Modified: 2024-09-04 - URL: https://prophetstor.com/amazon-eks-azure-aks-google-gke/ Popular Public Cloud ServicesAmazon EKS (Elastic Kubernetes Service), Azure AKS (Azure Kubernetes Service), and Google GKE (Google Kubernetes Engine) are popular managed Kubernetes services that provide an easy way to deploy, manage, and scale containerized applications in the cloud. With a wide variety of readily available instance types, they enable DevOps teams to easily scale up or down to handle changes in requirements or popularity spikes, reducing the risk of resource shortages when operating. Benefits of Federator. ai employed for Optimization of Public Cloud ServicesContainer adoption can introduce operation agility but also significant operational overhead, especially when managing compute resources across on-premises, hybrid cloud, MultiCloud, or edge architectures. To address this challenge, Federator. ai offers an AI-powered solution that optimizes container resources in public clouds. Diagram: Federator. ai takes the monitored data and provides the operation recommendations for different layers Multi-layer Visibility and OptimizationLeverage collected metadata and operational metrics from multi-layer infrastructure operations to provide ongoing, Just-in-Time Fitted recommendations for optimized resource orchestration using AI-powered workload predictions. Resource Utilization and Cost ImprovementAuto-scale container resources based on real-time application demands. Identify workload patterns and recommend the most cost-effective portfolio of instance types and quantities, enhancing resource utilization, eliminating over-provisioning, and supporting sustainability. Performance Assurance and ResilienceUse Federator. ai’s patented Cascade Causal Analysis to identify resource correlations among hardware, cloud resources, Kubernetes layers, and applications. This enables efficient allocation of resources to mission-critical applications while minimizing resource usage. Policy-compliant AutomationAutomate continuous operation optimization by accurately interpreting metadata and predicting workloads, then automatically... --- - Published: 2023-05-22 - Modified: 2024-09-04 - URL: https://prophetstor.com/vmware-vsphere/ Popular VM PlatformVMware vSphere is a popular virtualization platform that provides a flexible infrastructure for running a wide range of workloads. With vSphere, businesses can easily manage their virtual machines, storage, and networking from a single centralized location. Benefits of Federator. ai employed for Optimization of VMware vSphereManaging a large vSphere deployment can be a challenging task. Performance and cost issues can arise due to misconfiguration, over-provisioning, and other factors. To address these challenges, Federator. ai provides an AI-powered solution for optimizing vSphere operations. Diagram: Federator. ai and VMware work together to improve infrastructure efficiency Visibility and Optimization of VM ResourcesLeverage collected metadata and operational metrics to gain real-time visibility into VM resource usage with Federator. ai. Quickly identify opportunities for optimizing clusters and nodes, enabling accurate provisioning to ensure operational resilience. Cost ImprovementOptimize infrastructure utilization with Federator. ai by providing accurate capacity projections and recommending optimal instance types and quantities. Assess the TCO of on-premises components, enabling executives to evaluate long-term costs and make cost-effective decisions. Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you Read More Whitepaper｜Optimizing VMware Operation with AI-powered Federator. ai: Boosting Efficiency, Performance, and Cost Savings in Virtual Infrastructure Management --- > Federator.ai optimizes Amazon EC2 with AI for performance and cost efficiency, tackling misconfiguration and over-provisioning. - Published: 2023-05-22 - Modified: 2024-09-04 - URL: https://prophetstor.com/amazon-ec2/ Popular AWS Instances for VMsAmazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. Amazon EC2 provides virtual machines, known as instances, which can run a variety of operating systems and software applications, providing a scalable and flexible infrastructure for running workloads of all sizes. Benefits of Federator. ai employed for Optimization of Amazon EC2Managing a large Amazon EC2 deployment can be a challenging task. Performance and cost issues can arise due to misconfiguration, over-provisioning, and other factors. To address these challenges, Federator. ai provides an AI-powered solution for adding application-aware optimization to Amazon EC2. Diagram: Federator. ai and Amazon CloudWatch work together to configuring new VM clusters Visibility and Optimization of VM ResourcesLeverage collected metadata and operational metrics to gain real-time visibility into VM resource usage with Federator. ai. Quickly identify opportunities for optimizing clusters and nodes, enabling accurate provisioning to ensure operational resilience. Cost ImprovementOptimize infrastructure utilization with Federator. ai by providing accurate capacity projections and recommending optimal instance types and quantities. Assess the TCO of on-premises components, enabling executives to evaluate long-term costs and make cost-effective decisions. Start for FREE Free to create 10 VM's (node + namespace + controller) Request Demo Schedule a demo for you --- > Federator.ai provides comprehensive monitoring and analysis of data across various technology domains, including applications, infrastructure, data, network, and security. - Published: 2023-04-19 - Modified: 2024-09-04 - URL: https://prophetstor.com/cyber-security-application/ Federator. ai provides advanced tools to optimize security applications across domains like applications, infrastructure, data, networks, and security. These tools enable businesses to monitor data, identify vulnerabilities, and detect threats. By proactively optimizing security, Federator. ai enhances cybersecurity, offering stronger protection against cyber threats. Efficient Resource Planning and OptimizationLeverage machine learning and multi-layer correlations for tailored, application-aware resource orchestration and allocation. Automatically scale connected applications to ensure optimal performance, eliminate bottlenecks, and reduce operating expenses. Anticipate workloads and use resource correlation models to give users actionable insights for optimization. Making the Most of Operational MetadataTransform large volumes of operational metadata into optimized operations with Federator. ai's unique analysis. Enable data-driven decisions for IT/cloud operations and cybersecurity, enhancing automation, resilience, and sustainability. Leverage untapped metadata to optimize resource allocation, boost security readiness, and improve overall business performance. Scalability and seamless integrationIntegrate Federator. ai seamlessly into existing data center infrastructure to enhance energy efficiency and IT/cloud operations cost-effectively. Its scalability supports growing businesses by expanding resource management capabilities, offering long-term value and agility. This ensures a robust and secure environment for rapidly expanding organizations. Read More Transforming IT and Cloud Operations with Federator. ai: Applied Observability and Deep Insights for Cybersecurity Whitepaper CrystalClear by ProphetStor: Transforming Time Series Forecasting for Microservices Management Whitepaper Cloud Cost Management with ML-based Resource Predictions (Part II) Blog --- > With the help of machine learning-based analysis, Federator.ai can classify workload patterns for individual applications in no time, after receiving historical data, and offer appropriate portfolios of cloud instances to fit application demands. - Published: 2023-04-19 - Modified: 2024-09-04 - URL: https://prophetstor.com/optimal-cloud-instance-combinations/ Cloud instances provide flexible and scalable workload management, allowing new instances to be launched easily for application growth. However, launching the right types and quantities of instances is essential for optimal performance and cost savings. Federator. ai uses machine learning-based analysis to quickly classify workload patterns from historical data and recommend suitable cloud instance portfolios to meet application demands. It ensures optimal performance by providing the necessary resources—CPUs, memory, storage, and network capacity—and prioritizes the use of cost-effective reserved and spot instances to minimize costs. Federator. ai can achieve both the application resilience and cost savings by quickly identifying, classifying, and predicting the application workloads with its machine learning-based analysis Enhanced Application Resilience Identify application workload patterns and generate ML-based predictions to ensure optimal performance by allocating the right instance types at the right time. Optimized Cost Savings Maximize cost savings by prioritizing reserved and spot instances over on-demand ones, offering optimal portfolio recommendations that meet application demands while reducing procurement costs. A win-win sales strategy for MSPs Provide MSPs with tools to create lucrative instance portfolios that maximize margins and minimize end-user costs, fostering strong, long-term client relationships. Example Scenarios for MSP Video | Win-Win Sales Strategy for An MSP and Its End-Users https://youtu. be/9WqZMtNM26kProphetStor helps customers have a smooth journey without worrying about the complexity, cost, and support of application resilience. Federator. ai solves the seemingly contradicting objectives, and we can develop solutions based on ProphetStor’s advanced Federator. ai platform to add value to our services further. Cody... --- > 100% Green electricity and the adoption of Cloud resources are keys to lowering carbon footprint. Efficiency in cooling and consolidation of the servers make Data Center greener. - Published: 2023-04-19 - Modified: 2024-09-04 - URL: https://prophetstor.com/green-it-esg/ With the rise of Environmental, Social, and Governance (ESG) concerns, data centers and their users are seeking ways to reduce energy consumption, lower carbon emissions, and improve their ESG performance. While some focus on sourcing green electricity, like Amazon, Microsoft, and Google, most prioritize optimizing server over-capacity and underutilization. Federator. ai helps data centers save up to 50% on energy costs while enhancing application sustainability and meeting ESG requirements. It leverages data from servers, storage systems, network devices, and power distribution units to provide actionable insights, enabling informed decisions on resources and energy usage. By identifying wasted computing resources and recommending efficient allocation of compute instances for machine learning applications, Federator. ai reduces energy consumption, carbon footprint, and operating costs, helping data centers achieve their sustainability goals. ProphetStor's Energy Efficiency and Planning Solution for Data Center Operations Collect workload data using software sensors, then provide recommendations and execute power and cooling consumption adjustments accordingly Increase Energy Efficiency and SustainabilityUtilize real-time monitoring and analysis to identify areas for improvement, reduce energy consumption, and support reinvestment in sustainability initiatives. Maximize Cost Savings through Accurate Energy ForecastsLeverage machine learning algorithms for accurate energy consumption forecasts, providing detailed reports to identify waste and actionable steps to reduce energy bills. Facilitate Effective Management with Timely AdjustmentOffer a comprehensive view of energy consumption and real-time alerts, enabling data center operators to seize energy-saving opportunities. Deliver Targeted Recommendations for Energy ReductionProvide specific recommendations for energy efficiency, from adjusting server room temperatures to reconfiguring network infrastructure. Monetize Excess Carbon... --- > A streamlined and optimized IT infrastructure is critical for success in today's competitive corporate world. - Published: 2023-04-17 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/adding-application-aware-optimization-to-vmware-tanzu/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Brief Synopsis A streamlined and optimized IT infrastructure is critical for success in today's competitive corporate world. VMware Tanzu and Tanzu Kubernetes Grid Integrated (TKGI) Edition have emerged as significant Kubernetes management solutions. However, even with their robust capabilities, there remain gaps in resource optimization and application management. This is where Federator. ai, a data-driven AI solution with proprietary multi-layer correlation technology from ProphetStor, bridges the gap by providing application-aware optimization. This whitepaper explores the distinct advantages of combining VMware Tanzu, TKGI, and Federator. ai to improve infrastructure management, strengthen security and compliance, and support hybrid and multi-cloud strategies. By integrating Federator. ai with VMware Tanzu, organizations can achieve higher performance, efficiency, and cost savings across their Kubernetes environments. Overview of VMware Tanzu and Tanzu Kubernetes Grid Integrated (TKGI) Edition VMware Tanzu is an all-in-one Kubernetes platform designed to modernize both applications and infrastructure. Tanzu Kubernetes Grid Integrated (TKGI) Edition is a critical component that simplifies Kubernetes management and deployment across MultiCloud environments. Together, Tanzu and TKGI provide a framework for creating, managing, and upgrading clusters, ensuring consistent Kubernetes operations across on-premises, public cloud, and edge environments while minimizing operational complexity. Additionally, they offer automated patching and upgrades to enhance security and compliance, as well as optimize performance and resource consumption through cluster and resource scalability. Federator. ai: ProphetStor's Patented Multi-Layer Correlation Technology's Unparalleled Benefits Federator. ai is a machine learning-enabled solution that optimizes IT operations, resource allocation, and administration in Kubernetes environments. Its innovative multi-layer correlation technique stands... --- > Explore why CrystalClear Time Series Analysis Engine, outperforming Facebook Prophet and LinkedIn Greykite, translates to more precise predictions, faster decision-making, and cost savings. - Published: 2023-04-10 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/crystalclear-by-prophetstor/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Brief Synopsis Compared to its competitors, Facebook Prophet and LinkedIn Greykite, ProphetStor's CrystalClear Time Series Analysis Engine is a new technology offering excellent performance in workload forecasting and resource management for microservices. This white paper highlights the benefits of the CrystalClear Time Series Analysis Engine, highlighting its lower Mean Average Percentage Error (MAPE) values and shorter average runtime, making it a perfect investment opportunity for potential investors seeking cutting-edge technology. Introduction In today's fast-paced digital world, businesses increasingly rely on microservices for efficient, scalable, and reliable systems. Accurate workload predictions and resource management are critical for optimal performance and cost savings. In several areas, the CrystalClear Time Series Analysis Engine from ProphetStor is a game-changing technology that beats its competitors, Facebook Prophet and LinkedIn Greykite. CrystalClear Time Series Analysis Engine's Worth: CrystalClear is intended to deliver quick, accurate, and cost-effective predictions for microservice resource management. Its correlation-based prediction system outperforms Facebook Prophet and LinkedIn Greykite, especially when dealing with large cross-correlations between key workload measures and secondary metrics. Key Benefits Increased Prediction Accuracy: CrystalClear routinely delivers lower MAPE values, making more precise predictions. Businesses may benefit from better resource allocation and cost savings as a result. Quicker Predictions: CrystalClear has a shorter average duration than competitors, allowing for faster decision-making and resource management. Cost Savings: CrystalClear can cut the overall cost of resource management for firms by lowering the time and resources required for workload estimates. Table of Comparisons Under typical Azure2019 and Alibaba2021 workloads, the following table illustrates... --- > Enterprise CIOs face growing difficulties in managing complex IT and cloud operations while maintaining high levels of security and observability. - Published: 2023-04-10 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/transforming-it-and-cloud-operations-with-federator-ai/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Introduction Enterprise CIOs face growing difficulties in managing complex IT and cloud operations while maintaining high levels of security and observability. As modern companies attempt to optimize operations, maintain business continuity, and manage risks, applied observability and cybersecurity have emerged as critical components . With its unique innovations, ProphetStor Federator. ai establishes a new IT/Cloud resource management and cybersecurity standard . In this white paper, we will look at Federator. ai's unique capabilities, how they may transform how organizations manage their IT/Cloud operations and cybersecurity, and the untapped potential of operational metadata. Federator. ai's Patented Technology Provides a Competitive Advantage Depending on the application, resource planning and optimization Federator. ai's unique technology (US Patent No. 11579933) uses multi-layer correlations and machine learning to provide application-aware, multi-layer correlated resource allocation and optimization. This innovative method provides just-in-time, fitted resource orchestration and allocation, assuring application resiliency while lowering operating expenses. Federator. ai distinguishes itself from competing IT/Cloud resource management systems by anticipating application workload and developing resource correlation models, offering enterprises unprecedented insights to help them optimize their operations. Security visibility improves cybersecurity. Federator. ai's methodology is unique because it goes beyond IT/Cloud resource optimization to include security observability. Federator. ai monitors and analyzes data across several technology domains, including applications, infrastructure, data, network, and security, to provide helpful insight into potential vulnerabilities and threats. This comprehensive perspective enables firms to proactively identify and repair security risks, resulting in robust cybersecurity. As highlighted by Gigamon CEO Shane Buckley in , deep... --- > ProphetStor is a leading provider of IT/cloud operation optimization and application resilience solutions, with over 14 granted USA patents and 10+ patents pending. - Published: 2023-04-10 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/introduction-to-prophetstors-federator-ai/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon The Federator. ai Architecture ProphetStor is a leading provider of IT/cloud operation optimization and application resilience solutions, with over 14 granted USA patents and 10+ patents pending. Federator. ai is our advanced ML-based solution that enables predictive and prescriptive cascade causal analysis, automating optimization and sustainability in IT/cloud operations. By bridging the gap between corporate KPIs and resource provisioning APIs, we deliver proactive actions for mission-critical situations. Fedeartor. ai platform architecture is shown below: Figure 1: Federator. ai platform architecture Precision Operations Analytics Federator. ai from ProphetStor enables businesses to gain more accurate IT/Cloud operation insights. These insights enhance business procedures, marketing strategies, and user experience, improving overall performance. Federator. ai Increases Business Value ProphetStor helps businesses with digital transformation by aligning IT with business objectives, ensuring data availability, dependability, and security while maximizing cloud resources and saving costs. Our ML-based solutions help businesses meet KPIs and generate economic value, enabling Business Success Management (BSM). Our comprehensive approach to digital transformation enables businesses to realize the full potential of IT services. Selecting the Best KPI for Digital Transformation Digital transformation is about creating new value through innovative methods rather than simply lifting and shifting. We assist businesses in identifying their top transformation goals and selecting KPIs that will help them differentiate themselves from the perspective of investors, employees, and customers—the North Star concept. Our strategic KPI portfolio strategy helps businesses meet their KPIs while generating value. Operation Metadata Federator. ai from ProphetStor collects historical operation metadata from popular monitoring... --- > Check out ProphetStor's Federator.ai, an AIOps platform designed to enhance your virtualization environment with predictive analytics and machine learning. - Published: 2023-04-06 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/optimizing-vmware-operation-with-ai-powered-federator-ai/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Introduction This white paper aims to discuss the increasing complexity and scale of virtualized environments, emphasizing the need for intelligent resource management and optimization solutions. Federator. ai is an AI-powered solution that improves VMware infrastructure efficiency by providing insights and recommendations for resource allocation and application performance enhancement. We will review Federator. ai's integration with VMware environments, its use cases, and real-world success stories from customers who have improved resource utilization and saved money using Federator. ai. This white paper is intended for VMware customers, IT professionals, decision-makers, and application developers looking for AI-driven solutions to optimize their virtual infrastructure, improve application performance, and more efficiently manage resources. Figure 1: Federator. ai and VMware work together to improve infrastructure efficiency Integrating Federator. ai in a VMware Environment Federator. ai is a containerized application that runs on a Kubernetes cluster within VMware virtual machines. To reduce the effort of setting up a Kubernetes cluster to install Federator. ai, a VMware OVF template is available that includes a single-node Kubernetes cluster and Federator. ai. Users can download the VMware OVF template from ProphetStor and import it into their VMware vSphere Client. This allows users to deploy the OVF template to the VMware environment, launch the VM, and start using Federator. ai. By inputting essential configurations in the Federator. ai UI (such as the vCenter IP address and credentials needed for metric access), Federator. ai will commence collecting, analyzing, and providing recommendations for VMware VMs. Federator. ai Use Cases for VMware Customers... --- > Explore how the DataProphet Recommendation Engine uses advanced machine learning algorithms to optimize performance, reduce costs, and improve efficiency. - Published: 2023-04-06 - Modified: 2025-03-17 - URL: https://prophetstor.com/white-papers/the-patented-ai-powered-dataprophet-recommendation-engine/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Introduction Consider a world in which cloud operations are constantly optimized with the same level of intelligence and personalization as recommendation engines on social media and shopping websites. These recommendation engines have made our lives easier by recommending relevant content, products, or connections based on our preferences and behavior, allowing us to tailor our online experiences. ProphetStor's DataProphet Recommendation Engine applies the same intelligent recommendation technology to cloud computing, transforming the way we manage cloud operations, providing businesses with unrivaled value, and addressing the growing need for efficient cloud cost management. In this white paper, we will look at the challenges that businesses face when managing cloud operations and introduce ProphetStor's revolutionary DataProphet Recommendation Engine. This engine is the foundation for Federator. ai, a cutting-edge solution that optimizes cloud operations and integrates seamlessly with a variety of market solutions. We will also discuss the significance of ProphetStor's recently granted patent and how it enhances the DataProphet Recommendation Engine's capabilities. Finally, we'll look at how Federator. ai's FinOps benefits enable efficient cloud cost management, addressing concerns raised in a recent Wall Street Journal article. Part 1: Challenges in Cloud Operations Management In the era of cloud computing, managing cloud operations has become increasingly complex. Businesses must ensure cost-effective, resilient operations while also requiring comprehensive stack visibility. As organizations transition to Cloud Native architectures and Kubernetes-based container environments, these challenges intensify. 1. 1 East-West Dynamics and North-South PerspectivesEffective cloud IT infrastructure management necessitates a deep understanding of North-South Insight (IT infrastructure... --- > Prometheus and Federator.ai effectively manage IT systems with predictive analytics, application insight, autoscaling, and cost management for optimized operations. - Published: 2023-03-13 - Modified: 2025-03-18 - URL: https://prophetstor.com/white-papers/unlocking-the-power-of-operation-metadata-with-prometheus/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Abstract Organizations in today’s fast-paced world require a tool to manage and optimize their IT systems. Prometheus and ProphetStor's Federator. ai have effectively managed organizations’ current IT/Cloud operations. Prometheus and Federator. ai work together to provide predictive and prescriptive analytics, application insight, autoscaling, and cost management. This white paper shows how these tools can improve IT system management. Introduction Businesses in today’s digital world are constantly looking for better ways to manage their IT systems. However, managing IT/Cloud operations requires massive amounts of operation metadata. Prometheus and ProphetStor's Federator. ai can help in this situation. Prometheus is a time-series database and open-source monitoring system that collects metrics and generates alerts in cloud-native configurations. Federator. ai provides predictive and prescriptive analytics for application insights, auto-scaling, and cost management. Federator. ai recognizes trends, forecasts performance, and provides data-driven recommendations. It gathers and analyzes current and historical data from various sources, including Prometheus. Figure 1 Tuning the Operation Metadata into Optimized Operation Directives Prometheus and Federator. ai: Easy Integration The following figure 2 shows how simple it is for Federator. ai to connect to Prometheus as a data source. URL to Prometheus service is required, but the token is optional for authentication. Specify if you are using Federation, a group of Prometheus servers that send metrics to a centralized Prometheus server. In addition, users can specify historical data to be collected. It can significantly shorten the time-to-value. Once the connection is made, users can enjoy the integrated solution’s benefits. Figure 2 Using... --- > Explore how Chunghwa Telecom leveraged ProphetStor’s Federator.ai to overcome challenges of operations and achieve cost savings and Green IT objectives. - Published: 2023-03-09 - Modified: 2024-03-18 - URL: https://prophetstor.com/case-studies/a-case-study-with-chunghwa-telecom-and-prophetstor-federator-ai/ - 頁面分類: Case Studies Introduction Chunghwa Telecom is the largest telecom company in Taiwan, offering various services, including domestic and international fixed communication, mobile communication, broadband, and internet services. In addition to these traditional services, the company provides information and communication technology services to enterprise customers with big data, information security, cloud computing, and IDC capabilities. (https://www. cht. com. tw/en/home/cht) Chunghwa Telecom operates many virtual machines (VMs) in their data centers. Keeping the resilient operation of the VMs while identifying opportunities to reduce wasteful resources is one of the critical operational challenges faced by the company. This challenge requires Chunghwa Telecom to right-size VM resources accurately, providing a roadmap for cost savings while contributing to the sustainability goal of their infrastructure. However, traditional VM monitoring tools only provide passive resource usage. It is nearly impossible to achieve multiple goals without a solution that provides accurate, application-aware prediction spanning across layers of the infrastructure and resource recommendations to meet application demand in real time. This case study explores Chunghwa Telecom's success in achieving cost savings and Green IT objectives by leveraging ProphetStor's Federator. ai, including the reduction of predicted idle resources in VM clusters and accurate provisioning of VM resources for operation resilience. Additionally, the implementation process and results achieved through using Federator. ai will be discussed. Solution: Keep VM Resources Right-size and Minimize Waste Chunghwa Telecom had to ensure that its mission-critical applications in the data centers performed optimally and met its customers' service-level agreements (SLAs) while also optimizing costs, given the large number... --- > Discover how Federator.ai provides predictive analytics to help MSP and its end-users optimize usage of Amazon EC2 instances, leading to cost savings and improved performance. - Published: 2023-03-07 - Modified: 2025-03-18 - URL: https://prophetstor.com/white-papers/how-aws-msps-optimize-margin-and-customers-costs/ - 頁面分類: Whitepapers - Folder: Whitepapers Medium-Icon Introduction Cloud computing has revolutionized how businesses operate, enabling them to access powerful computing resources on demand without investing in expensive hardware and infrastructure. As a result, Amazon Web Services (AWS) has emerged as a leader in the cloud computing market, offering a vast array of services and options to businesses of all sizes. According to Statista, as of the fourth quarter of 2022, AWS held the largest share of the worldwide cloud infrastructure market at 32%, which is significantly higher than its two closest competitors, Microsoft Azure (23%) and Google Cloud (10%). Managed Service Providers (MSPs) are critical in providing AWS cloud services to end-users. MSPs can resell cloud instances, including On-Demand Instances, Reserved Instances, and Spot Instances, or provide value-added services to customers who are AWS users. However, selecting the optimal combination of instances to support an application with persuasive costs and benefits to MSPs’ revenue can be challenging. That’s where Federator. ai steps in to help. Federator. ai is a cloud operation optimization platform that leverages advanced analytics to optimize AWS resource usage, reduce costs, and support application resilience. Its most straightforward application uses predictive and prescriptive analytics to understand workloads and determine the most efficient combination of On-Demand, Reserved, and Spot instances to support the application while minimizing costs. By leveraging Federator. ai’s analytics capabilities, MSPs can help their customers optimize their cloud resource usage and provide more efficient and effective cloud services. This, in turn, can result in significant cost savings for the MSP... --- > Explore how Federator.ai optimizes the infrastructure, enhances application resilience, reduces cloud costs, and achieves Green IT for P Bank. - Published: 2023-03-02 - Modified: 2024-03-18 - URL: https://prophetstor.com/case-studies/federator-ai-significantly-reduces-cloud-spend-and-carbon-footprint-at-p-bank/ - 頁面分類: Case Studies Overview P Bank is a leading European bank with a strong global presence. The bank has a history dating back to 1822 and has evolved to become one of the world’s largest financial institutions, offering a range of financial products and services to clients across the globe. P Bank strongly focuses on sustainability and has made significant efforts in recent years to reduce its environmental impact, including setting ambitious targets to reduce its carbon footprint. In recent years, P Bank has recognized the importance of digital transformation in its operations and has invested heavily in developing its digital capabilities. As part of this transformation, the bank has adopted Kubernetes as a critical technology for its containerized workloads, providing the flexibility, scalability, and reliability required for modern applications. Challenges in Cloud Operations: Addressing High Costs and Environmental Sustainability Goals P Bank faced the challenges of optimizing its Kubernetes infrastructure, reducing costs on the IKS platform, and reporting the saving of carbon footprint. To address this challenge, the bank required advanced analytics capabilities to predict and optimize future resource usage patterns, minimize over-provisioning and underutilization, and ensure application resilience in the face of dynamic workloads - a critical requirement for a financial institution. As an example, one of the bank’s Kubernetes clusters consisted of 15 worker nodes and a total of 27 nodes running Kubernetes 1. 13, with a total of 252 vCPU and 1500 GB memory, and it supported 135 namespaces and more than 2,000 pods. In addition, the bank was... --- > Unleash the full potential of AI with Federator.ai's patented multi-layer correlation technology to boost ESG compliance and lower costs in data centers. - Published: 2023-02-06 - Modified: 2024-03-18 - URL: https://prophetstor.com/white-papers/innovative-ai-solution-for-data-centers/ - 頁面分類: Whitepapers - Folder: Whitepapers Abstract Federator. ai is leading the way in sustainable data center management with its innovative, patented multi-layer correlation technology and machine learning capabilities. This cutting-edge solution provides data centers with a comprehensive approach to reducing energy consumption, optimizing computing resources, and minimizing their carbon footprint. With the ability to save up to 50% on energy costs and improve the sustainability of applications, Federator. ai is the ideal solution for businesses looking to meet ESG requirements and promote a more environmentally conscious approach to data center management. Proactive monitoring, maintenance features, and automation capabilities ensure that systems are functioning optimally and efficiently, making Federator. ai the clear choice for responsible, high-performing data center management. Introduction Data centers play a vital role in modern businesses, providing the infrastructure for various online applications, cloud computing services, and big data analytics. However, as data continues to grow exponentially, data centers consume a growing amount of energy, resulting in high operating costs and environmental impact. To meet the increasing energy efficiency and sustainability demand, data centers need to optimize their energy consumption and reduce their carbon footprint. Figure 1 Data Center Cost and Carbon Footprint To address this challenge, ProphetStor offers an innovative energy efficiency and planning solution for data centers. Our solution leverages our patented multi-layer correlation technology with Machine Learning to help data centers understand the behavior of their applications in the past and future. By analyzing data from various sources within the data center, such as servers, storage systems, network devices, and... --- > Discover how Federator.ai helped a networking hardware & software company effectively manage cloud resources and achieve over 80% in estimated cumulative savings. - Published: 2023-02-03 - Modified: 2024-03-18 - URL: https://prophetstor.com/case-studies/federator-ai-helps-networking-company-manage-cloud-resources/ - 頁面分類: Case Studies Overview A multinational corporation and leading provider of networking products and services including wireless access points, routers, switches, network management software, and network security products. The company's main focus is providing networking solutions for service providers, enterprise customers, and data center operators. The company offers cloud-based network management solutions for its customers to manage their on-prem networking devices. The company’s cloud infrastructure supports millions of networking devices with over $20M of annual public cloud spending. Challenge: High Cloud Costs without Visibility for Optimization The company has been struggling with managing and optimizing its cloud resources. The company was facing the challenge of over-provisioning of cloud resources which leads to high cloud costs, and also difficulty in understanding how its resources were being used. This made it difficult for the company to make informed decisions about resource allocation, which resulted in inefficiencies and higher costs. Solution: Intelligent Data-Driven provisioning of resources ProphetStor's Federator. ai is an AI-based data management platform that provides a single, unified view of resource usages of multiple clusters. The platform uses machine learning algorithms to analyze data and identify patterns of application workload, and it can automatically optimize resource usage, resulting in improved efficiency and reduced cloud costs, which is exactly the crucial trending technology of ‘Applied Observability’ proposed by Gartner. The company implemented Federator. ai to better manage and optimize its cloud resources. Since implementing Federator. ai, the company has seen a number of benefits, including: Improved visibility into cloud resources, which has helped the company... --- > See how companies have transformed their Cloud journeys with the help of ProphetStor to achieve efficiency, cost savings, and performance upgrades. Browse now. - Published: 2023-01-18 - Modified: 2024-06-24 - URL: https://prophetstor.com/case-studies/ Orange Leverages Federator. ai for Automated Resource Management and Green IT to Meet EU Corporate Sustainability Regulations Orange Leverages Federator. ai for Automated Resource Management and Green IT to Meet EU Corporate Sustainability Regulations Facilitate Cost Optimization 30% of cloud costs reduced within the first three months Enhance Utilization of Resources Applications meet SLA without over-provisioning of resources Meet Sustainability Requirements Improve energy efficiency for the reduction of carbon footprint Read Customer Story A GPU-based Supercomputer Sees 60% Increase in Utilization with Federator. ai Improve Performance with Minimal Costs Optimize performance and save up resources by 60% Complete Overview of Resource Allocation Make informed decisions with GPU usage predictive graphics Boost Efficiency with Anomaly Detection Real-time resource monitoring for optimal operational efficiency Read Customer Story A GPU-based Supercomputer Sees 60% Increase in Utilization with Federator. ai Federator. ai Brings a Pleasant Journey of a World-leading Research and Advisory Company in Moving to MultiCloud with Kubernetes Federator. ai Brings a Pleasant Journey of a World-leading Research and Advisory Company in Moving to MultiCloud with Kubernetes Savings with MultiCloud Strategy Optimize resources and costs for each application with up to 60% savings Upgrade Performance Reduce application latency by up to 70% for a wide range of workloads Proactive Management Handle the complexity of Kubernetes in an integrated manner Read Customer Story How Federator. ai is Helping a Leading Networking Company Improve Cloud Resource Management Get a Clear Picture of Cluster Resource Usage Streamline the management of multiple clusters with our intuitive, single-pane-of-glass... --- > Discover a research firm's successful move to MultiCloud and improved efficiency, cost savings, and performance with Federator.ai. - Published: 2023-01-18 - Modified: 2024-03-18 - URL: https://prophetstor.com/case-studies/pleasant-journey-of-a-research-and-advisory-company-in-moving-to-multicloud/ - 頁面分類: Case Studies Overview One of the world’s most influential research and advisory firms, headquartered in Cambridge, MA. The NASDAQ listed company provides unique insights that is grounded in annual surveys of more than 675,000 consumers and business leaders worldwide, rigorous and objective methodologies, and the shared wisdom of their innovative clients. As they grow their business, their IT operates with ten different DEV teams in diversified regions for various products and solutions. With a large environment and data center expansion through acquisition, their IT team has strived to understand how to meet the application SLA with minimized cost and enhanced performance. Furthermore, labor-intensive operational tasks consumed the team, leaving the questions of how to formulate the IT infrastructure to support the next phase of business expansion unanswered. After several months of careful studies, they decided to adopt the containerized MultiCloud infrastructure solution with Kubernetes to automate labor-intensive tasks, scale as the business grows, and optimize their cloud spending. They found that they have heavy usages of NGINX, node. js, and Redis, among other services for the containerized applications. They adopted a microservices-based approach using containers and Kubernetes orchestration. Their developers are in the process of moving initial parts of its infrastructure and new services to Kubernetes. Administrators love the simplicity of setting up new clusters with a single command and managing and balancing workloads on thousands of containers at a time. They can also manage data access down to a fine-grained level, eliminating the need to set up duplicate machines for security... --- > See how Federator.ai helps a national-level super-computing center in Taiwan make an intelligent allocation to save up to 60% of resources. - Published: 2023-01-17 - Modified: 2024-03-18 - URL: https://prophetstor.com/case-studies/a-gpu-based-supercomputer-sees-60-increase-in-utilization/ - 頁面分類: Case Studies Overview A national-level super-computing center in Taiwan possesses a large computing and networking platform facilities for use by domestic academia and general public. A major supercomputer at the center provides the Taiwan computing cloud service through managed container services via Openshift. ProphetStor entered into contract with the center to deliver Federator. ai on those servers to monitor/ predict just GPU usages, in the first stage. The center is expected to standardize Federator. ai as part of its resource optimization solution across all clouds. Challenge: Tremendous Computing Power Waste Being a government official organization, it provides an AI development platform to support the research and development of the “digital country” for Taiwan. Also, the center promotes industry-university collaboration, conducts forward-looking research and development of smart technologies, big data, artificial intelligence applications, and plans to build a national AI R&D center and cloud service foundation to provide related application services. One of the critical issues is that the AI initiatives’ workloads and their assigned GPU core resources are often incompatible, resulting in a massive computing power waste. The resources’ planning and scheduling are done by guesswork or based on the users’ requests, mostly over-provisioning, rather than the real future workloads. To maximize the utilization and have cost-effective operation becomes the central pain point, and they need to resolve quickly. Solution: Federator. ai provides AIOps solution for optimized planning and allocation ProphetStor’s Federator. ai® is a patented, AI-enabled solution that provides predictive analytics needed for the GPU-based supercomputer’s effective operation at the center.... --- > Learn how Orange optimized its resource management and automation with ProphetStor's MultiCloud solution to achieve cost savings and Green IT. - Published: 2023-01-16 - Modified: 2024-03-18 - URL: https://prophetstor.com/case-studies/telecom-automates-resource-management-and-optimization-on-multicloud/ - 頁面分類: Case Studies Overview Orange, a major telecommunications company with operations across Europe, Africa, and the Middle East, is committed to delivering advanced and reliable services to its 260 million customers worldwide. (https://www. orange. com/en) Orange has adopted a cloud-first approach and rapidly migrated its IT infrastructure to the cloud as part of its digital transformation strategy, which helps take advantage of the scalability, flexibility, and cost savings that come with cloud computing. However, this increased complexity and difficulties in managing and optimizing its cloud operations and meeting sustainability regulations. Challenge: Automating Resource Management and Meeting Sustainability Regulations The Orange cloud team has been building a Kubernetes-based platform to support developing and deploying new applications from various business units. However, as the number of applications grows, the cloud team faces the challenge of allocating and managing resources required for each one at scale and supporting the resilience of operations while minimizing the waste for Green IT. This lack of visibility and optimization of resources can lead to over-provisioning, excessive cloud costs, and poor application performance. Moreover, with the new EU Corporate Sustainability Reporting Directive, Orange must report on social and environmental risks and impacts of activities on people and the environment and disclose information on sustainability performance. In this context, Green IT is becoming an essential requirement for large companies and listed companies. Orange needs to ensure that its cloud operations meet these regulatory requirements. Solution: Federator. ai for Automated Resource Management and Green IT Orange tackled the challenges of managing cloud operations... --- > Unlock the potential of AI/ ML with ProphetStor’s Federator.ai which offers data management, Applied Observability and analytics solutions for biz to stay ahead in the game. - Published: 2023-01-09 - Modified: 2025-05-06 - URL: https://prophetstor.com/federator-ais-ai-ml-technologies-for-the-future/ As businesses continue to digitalize and adopt new technologies, the need for effective data management and observability becomes increasingly important. According to Gartner, AI and Machine learning applied systematically will be a major technology trend in 2024 and beyond. And Applied Observability, captured and analyzed by AI for recommendations for faster and more accurate future decisions, is a key trend for businesses to stay ahead in the digital age. Why Federator. ai Can Manage Data in Modern IT Operations Federator. ai enables 'Applied Observability' by providing insights across multiple monitoring data sources, multi-layer infrastructure, and MultiCloud environments. With our patented AI and machine learning technologies, Federator. ai offers an innovative approach to predicting system resource requirements and managing resources through multi-layer correlations. This capability allows for effective prediction of changes in application workloads and deployment of resources at future time points to meet operational needs. These unparalleled observability and optimization capabilities provide businesses with deep insights into their data, allowing them to make informed, data-driven decisions that bridge the gap between corporate KPIs and resource provisioning APIs. What Makes Federator. ai So Powerful Federator. ai's three pillars that make businesses truly harness the power of their data to drive innovation and success:Automation, Performance Enhancement, and Cost Optimization. AutomationKey for businesses to streamline their processes and increase efficiency Its AI and machine learning capabilities allow for automated data collection and analysis, saving time and resources for businesses. It allows for automatic alerts and notifications to be sent when certain thresholds are... --- - Published: 2022-11-21 - Modified: 2024-05-30 - URL: https://prophetstor.com/demo-request-submitted/ Your demo request for Federator. ai has been sent. Thank you for your interest in Federator. ai. Before our team contacts you with further information, we suggest visiting our FAQ page, Intro/ Demo Videos, Seminar/ Webinar Videos or Whitepapers. These resources will provide a quick overview of the benefits of Federator. ai and help you understand how its features can address the critical issues you are facing. FAQ Whitepapers Intro/ Demo Videos Blog Seminar/ Webinar Videos Infographics FAQ Intro/ Demo Videos Blog Whitepapers Seminar/ Webinar Videos Infographics Home --- > Leave your contact information for us to schedule a demo by our engineers and see how Federtor.ai can help your business optimize both cost and performance KPIs. - Published: 2022-11-18 - Modified: 2024-06-26 - URL: https://prophetstor.com/request-demo/ Request a demo of Federator. ai Please fill out the form to the right to request a demo, and also check out our intro/ demo videos and FAQ page for more information. We will contact you to schedule a demo for you soon. Feature Demo Video More Intro/ Demo videos » Q: which resources are appliable to run Federator. ai? Resources like CPU, memory, storage, and network bandwidth running on top of VMware vSphere, Tanzu, AWS, Azure, Google Cloud, and IBM Cloud can be visualized, predicted, and optimized. Q: Does Federator. ai fit my company’s needs? No matter you are suffering from managing the patchwork of legacy and cloud technology, enduring the concerns of opportunity cost with the infrastructure upgrade, or struggling with the migration from one cloud to another, Federator. ai is an excellent AIOps tool to help. More FAQ » Q: which resources are appliable to run Federator. ai? Resources like CPU, memory, storage, and network bandwidth running on top of VMware, AWS, Azure, Google Cloud, and IBM Cloud can be visualized, predicted and optimized. Q: Does Federator. ai fit my company’s needs? No matter you are suffering from managing the patchwork of legacy and cloud technology, enduring the concerns of opportunity cost with the infrastructure upgrade, or struggling with the migration from one cloud to another, Federator. ai is an excellent AIOps tool to help. More FAQ » --- > If you cannot get technical answers from our demo videos and documents, please fill out the form to the right and our senior engineer will contact you ASAP. - Published: 2022-11-04 - Modified: 2022-12-05 - URL: https://prophetstor.com/contact-technical-support/ Contact Technical Support We’ve got plenty of demo videos and documents that help you download and set up Federator. ai. If you still have specific technical questions or comments, please fill out the form to the right and our senior engineer will contact you ASAP. Setup Video Video about how to install and configure Federator. ai More Videos » Installation Guide Federator. ai Release v5. 1. 0 Installation Guide More Installation Guide » User Guide Federator. ai version 5. 1 User Guide More User Guide » Please enable JavaScript in your browser to complete this form. Name *FirstLastEmail *Phone Number (Please add international call prefix) *Subject *Issue or question *GDPR Agreement *I consent to having this website store my submitted information so they can respond to my inquiry. *Submit --- > It collects our presentation videos in seminars or webinars of the grand gathering. Federator.ai were introduced clearly and concisely to the elites in the industry. - Published: 2022-11-02 - Modified: 2024-01-18 - URL: https://prophetstor.com/seminar-webinar-videos/ Kafka Summit Americas 2021 – Intelligent Auto-scaling of Kafka Consumers with Workload Prediction A presentation in Kafka Summit on why intelligent autoscaling is better than Kubernetes native HPA. Using machine-learning based forecasting, scaling the Kafka consumers could be achieved in a more timely manner, resulting with better performance KPI's. Joint webinar with Datadog: Understanding and Rightsizing Container Resources With Datadog and Prophetstor In this webinar, we show how Datadog and ProphetStor help teams to solve the challenges in deploying containerized applications on OpenShift by bringing end-to-end visibility and resource optimization recommendations to meet application performance and cost requirements. Learn More » OpenShift TV program: AI-Enabled Proactive Management for Cost and Performance Optimization in Hybrid MultiCloud The recording and detailed presentation material illustrating how ProphetStor provides the solutions and how it brings customers’ values to optimize the cost and performance in Hybrid MultiCloud operations. Learn More » Federator. ai for Optimizing Resource Management on OpenShift A joint webinar with Red Hat on how Federator. ai facilitates and optimizes resource management for sustainable operations on OpenShift. Red Hat Summit 2019 – ProphetStor Federator. ai Demo ProphetStor's Federator. ai demo at Red Hat Summit 2019. It showed how Federator. ai utilizes its machine learning technology to simplify cost optimization process for both Day1 deployment and Day2 operation. Try Federator. ai for FREE to create 10 objects (node + namespace + controller) Start for FREE Kafka Summit Americas 2021 – Intelligent Auto-scaling of Kafka Consumers with Workload Prediction A presentation in Kafka Summit on... --- > The videos here contain an introduction to Federator.ai, a feature demo, reviews from clients, integration with other monitoring services, MSP strategy, etc. - Published: 2022-11-01 - Modified: 2024-09-02 - URL: https://prophetstor.com/intro-demo-video/ Federator. ai Federator. ai GPU Booster Feature DemoProphetStor Federator. ai GPU Booster optimizes GPU resources on Kubernetes with patented algorithms. Perfect for businesses using high-end NVIDIA GPUs, it streamlines GPU management, especially for MultiTenant AI model training. Maximize GPU utilization, boost training throughput, and keep your AI initiatives ahead with Federator. ai GPU Booster. Learn More » Federator. ai Feature DemoProphetStor Federator. ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for the applications on Kubernetes. Using advanced machine learning algorithms to predict application workloads, Federator. ai scales the appropriate amount of resources at the right time for optimizing application performance and achieving cost savings. Learn More » Federator. ai Optimizes Kubernetes for Cost and PerformanceProphetStor’s Federator. ai uses predictive analytics to analyze the dynamic workloads of Kubernetes applications and optimizes resource usage and performance in private, public, hybrid or multicloud environments. Learn More » Win-Win Sales Strategy for An MSP and Its End-UsersWith the help of ProphetStor’s MSP Operation Recommender, an MSP not only can formulate its convincing sales strategy for Reserved Instances to achieve its revenue growth and cost optimization for its end-user but can also offer value-added consulting services to get upsell opportunities and gain customer loyalty. Eventually, a win-win scenario proposed by Federator. ai benefits both sides. Learn More » Federator. ai and Sysdig IntegrationBy integrating operation metrics collected by Sysdig, Federator. ai, an ML-based platform, provides accurate predictions and just-in-time recommendations for resource allocation and autoscaling, and eliminates complexity and uncertainty... --- > A quick video tutorial on installing Federator.ai from different sources and a step-by-step demo for the initial setup to have great management on Kubernetes. - Published: 2022-10-28 - Modified: 2024-08-23 - URL: https://prophetstor.com/setup-video/ Federator. ai Stack optimizes the Time-to-Online of GPU serversFederator. ai Stack offers a complete toolset for efficient AI/ML training. Its one-step installation simplifies setup, ensuring all essential AI software is ready to use, enabling smooth operation of the Federator. ai GPU Booster for optimized GPU utilization. How to Configure An Application on Federator. ai for Autoscaling Kafka ConsumerA quick description of how to achieve better performance and lower cost by auto-scaling Kafka consumers in Kubernetes environment, and a demo of how to configure an application on Federator. ai for Kafka consumer. Installing Federator. ai from Red Hat MarketplaceA quick tutorial on installing Federator. ai from Red Hat OpenShift Marketplace, including registering the cluster to Red Hat Marketplace, subscribing and installing Federator. ai, and setting up the configuration for the target cluster and its applications. Installing Federator. ai from SUSE/Rancher MarketplaceA quick tutorial on installing Federator. ai from SUSE/Rancher Marketplace, including installation and the setup of Federator. ai to manage the target cluster and its applications. ProphetStor Federator. ai CI/CD Integration with TerraformLearn how to integrate Federator. ai with Terraform to automatically and dynamically provision your containers with the right amount of resources that maintains performance objectives while reducing the cost. ProphetStor Federator. ai Installation and ConfigurationA quick tutorial on downloading installation script from GitHub, installing Federator. ai, and setting up the configuration on the web browser to manage a Kubernetes or VM cluster and its applications. Federator. ai Stack InstallationFederator. ai Stack offers a complete toolset for efficient AI/ML training.... --- > 100% Green electricity and the adoption of Cloud resources are keys to lowering carbon footprint. Efficiency in cooling and consolidation of the servers make Data Center greener. - Published: 2022-08-16 - Modified: 2023-04-26 - URL: https://prophetstor.com/green-it-esg/ Global Data Center Consumption (Source: International Energy Agency) Why We Need Green IT for Cloud According to estimation on GO CLIMATE, the carbon footprint of servers are: Cloud server using 100% green electricity: 160 kg CO2e / year and server Cloud server using non-green electricity: 458 kg CO2e / year and server On premise or data center-server using 100% green electricity: 320 kg CO2e / year and server On premise or data center-server using non-green electricity: 916 kg CO2e / year and server 100% Green electricity and the adoption of Cloud resources are keys to lowering carbon footprint and going Green IT. It is recommended that the tech enterprises adopt a policy of secure, 100% sustainably-powered servers for data centers (for example: solar, wind, hydro or nuclear), 100% sustainable locations for new Cloud instances (e. g. use Azure, Google Cloud or the sustainable AWS in specific regions) and transition existing VMs there as soon as possible. How to Make Greener Operations Efficiency in Cooling Since cooling takes a big part of a data center's energy consumption, scaling the cooling based on server workloads is crucial measures instead of the same cooling for all. Consolidation of the Servers Instead of powering on servers for low workloads, consolidating the workloads and hibernating inactive servers for a data center to maximize the usage of each server is much greener. How Federator. ai Helps Go Green Federator. ai, an AIOps platform, utilizes its patented ML-based prediction engine to accurately predict the workloads and direct resources only... --- > Based on predictions for individual application workload and resource usage, Federator.ai helps users achieve much better performance with fewer resources. - Published: 2022-06-20 - Modified: 2024-09-03 - URL: https://prophetstor.com/application-acceleration/ Using the machine learning capabilities of CrystalClear Time Series Analysis Engine, Federator. ai predicts application workload dynamics to scale containers/pods (replicas) and provides Just-in-Time Fitted allocation recommendations. By leveraging application-aware insights into individual applications metrics and CPU/memory usage, Federator. ai improves performance (e. g. , reducing latency in Kafka, lowering average response time & HTTP error rate in NGINX) while minimizing resource usage (e. g. , reducing Kafka consumers, optimizing CPU & memory management). Effective workload predictionsFocus on accurate indicators, like the message production rate of a Kafka topic, to generate precise workload predictions and ensure timely autoscaling for optimal performance. Cost-effective application deploymentsIntegrate workload metrics, predictions, and application KPIs to determine the optimal number of replicas, enabling more cost-effective application deployments. Achieving desired performanceEliminate the need for manual threshold setting in Kubernetes native HPA by automatically optimizing resource usage to meet desired performance targets. A presentation in Kafka Summit on why intelligent autoscaling is better than Kubernetes native HPA A demo of how to configure an application on Federator. ai for autoscaling Kafka consumer Not Just Cloud Cost Saving, Application Residence! Federator. ai is the only solution that takes care of saving the cloud cost and ensuring application resilience at the same time. Philip RobertsCEO of Cloudshape Read More Federator. ai Brings a Pleasant Journey of a World-leading Research and Advisory Company in Moving to MultiCloud with Kubernetes Case Study Intelligent Autoscaling of Kafka Consumers with Workload Prediction Blog Why Horizontal Pod Autoscaling in Kubernetes Needs to Be Application-Aware... --- > With an innovative AI engine, Federator.ai provides visibility of cloud operations for an optimal blend of cloud instances to benefit MSP and its end-users. - Published: 2022-06-17 - Modified: 2023-04-26 - URL: https://prophetstor.com/optimal-cloud-instance-combinations/ A Managed Service Provider (MSP) or a reseller of public cloud services faces many challenges in providing cloud instances proposals to end-users that reflect the real application resource demands with the most cost savings, and at the same time provide better revenue for the MSP. Challenges facing MSPs Low margin of on-demand instances sales High margin of Reserved Instances sales but need tools to convince the end-users to commit The balance between revenues and end-user savings is hard to achieve without dedicated professionals Discover and justify on-prem data center migration opportunities (digital transformation) Protect from pure spot price competition Value Propositions With an innovative AI engine, Federator. ai integrates with existing monitoring services and provides full-scale insights to all levels of resources in a cloud deployment. With Federator. ai, MSPs can formulate competitive strategies and strong relationships with the end users. Visibility of total cloud operations for an optimal blend of compute instances Federator. ai, with the awareness of the application-level operations, creates a meaningful classification of the workload placements to On-Demand, Reserved, and Spot instances. Taking into consideration of different discounts and margins, the MSP can achieve an optimal blend of instances for both the MSP and its end users. Effective recommendations for cloud operations to strengthen partnerships With the help of Federator. ai, an MSP can provide recommendations for application performance enhancement and resource planning that differentiates its positioning as a professional and beneficial business partner to its customers. The more the recommendations benefit end users’ cloud operations,... --- > Tapping into time series metadata, CrystalClear Analysis Engine produces predictions with high accuracy to achieve operation metrics from corporate KPIs. - Published: 2022-06-17 - Modified: 2023-02-23 - URL: https://prophetstor.com/crystalclear-time-series-analysis-engine/ CrstalClear Time Series Analysis Engine in Federator. ai analyzes past dynamic changes of resource metrics and forecasts future resource usage. With a correlation-based algorithm, it generates a large number of predictions in a short time with high accuracy; thus making it a low-cost solution for resource management for microservices. Using the primary workload metric of an application and the resource usage metrics of microservices of the same application, CyrstalClear Time Series Analysis Engine identifies the dependencies and correlation between the primary workload metric and all other microservice metrics and uses this knowledge to quickly generate the predictions of resource usage of microservices. It significantly reduces the time needed to generate these predictions compared to traditional time-series forecasting algorithms. How to speed up in CrystalClear Time Series Analysis Engine Read More Whitepaper｜ProphetStor’s CrystalClear Time Series Analysis Engine— Analytical Excellence Is All about Speed --- > Based on the results from the AI-powered predictions, DataProphet Recommendation Engine provides Just-in-Time Fitted resource provision for operations. - Published: 2022-06-17 - Modified: 2023-02-23 - URL: https://prophetstor.com/dataprophet-recommendation-engine/ ProphetStor’s DataProphet Recommendation Engine, based on the results from CrystalClear Time Series Analysis Engine, provides Just-in-Time Fitted resource provisioning recommendations for applications deployed on-prem or in the cloud so that the performance and cost of operations can be optimized in a machine-based, proactive manner. DataProphet Recommendation Engine handles North-South Insight (among layers of the IT infrastructure from application down to servers/Cloud instances) and East-West Dynamics (how the applications/ microservices react to the workload dynamics). It enables Federator. ai to be a true comprehensive platform that serves as a foundation for working with other market solutions. The full-scale insight of multi-layer correlations of the IT infrastructure (from application down to server/Cloud instance) by DataProphet Recommendation Engine Read More Whitepaper｜DataProphet: ProphetStor’s First-in-the-Industry Recommendation Engine for Cloud Operations Automation and Optimization --- > Federator.ai uses ML technology and produces recommendations that meet and exceed Gartner framework for managing and optimizing costs of Public Cloud IaaS/PaaS. - Published: 2022-05-11 - Modified: 2024-03-18 - URL: https://prophetstor.com/white-papers/cloud-cost-optimization-and-application-resilience-with-prophetstor/ - 頁面分類: Whitepapers How Federator. ai Meets Gartner Cloud Cost Management Guidance Framework and More ProphetStor's solution Federator. ai aims to solve the problems by using AI/ML technology and to produce recommendations that optimize the cost and performance. With predictive analytics, we can understand application behaviors from the metric data we collect from Prometheus, and other metric data sources. Utilizing the ability to know the trend and workload demands pattern, Federator. ai can autoscale applications in a more proactive and intelligent approach. For more information, please read the following presentation. Check out ProphetStor's demo video, please visit https://prophetstor. com/2022/03/02/federator-ai-feature-demo/ --- > Since there are too many application KPIs to understand and too many knobs to turn for optimization, a recommendation engine for AIOps is highly desired. - Published: 2022-05-05 - Modified: 2024-07-05 - URL: https://prophetstor.com/white-papers/first-in-the-industry-recommendation-engine-for-aiops/ - 頁面分類: Whitepapers - Folder: Whitepapers Image by ar130405 from Pixabay The world’s most influential digital platforms, such as Amazon, Netflix, Facebook, LinkedIn, etc. , constantly (machine) learn to offer better recommendations and advice. And it’s becoming clear that the best advice we now receive is more likely to come from intelligent machines than smart people . “Recommender systems are the most important AI system of our time, the most important machine-learning pipeline today. ,” Nvidia CEO and co-founder Jensen Huang said in Time Magazine in2021 . “Recommender systems predict your needs and preferences from past interactions with you, your explicit preferences, and learned preferences using collaborative and content filtering methods. ” Recommendation engines represent a global revolution in how choice can be personalized, packaged, presented, experienced, and understood. With recommendation engines (we will use Recommendation Systems and Recommendation Engines interchangeably) in the consumer world, people can make impactful decisions based on the deeper insights and recommendations unseen before. However, although the recommendation engines are readily available in the consumer sector, the IT world is yet to have one that helps the user automate and optimize operations in Cloud, which is deemed complicated to do and requires certified cloud architects and engineers’ involvement. The State of Digital Transformation The IT industry has adopted the approach of containerized applications managed by Kubernetes for Digital Transformation. The apparent benefits enjoyed are agility, high performance, and flexibility matching the core ideas of Cloud Computing. However, the challenges are the complexity, missed visibility, compromised security, rising cloud usage cost, and... --- > The algorithm of prediction-based resource management is a novel concept that utilizes correlations for precise predictions with less resource & time consumption. - Published: 2022-04-06 - Modified: 2024-03-18 - URL: https://prophetstor.com/white-papers/correlation-based-predictions/ - 頁面分類: Whitepapers - Folder: Whitepapers Introduction Deploying applications in a serverless cloud platform or a Kubernetes system in the cloud has become a popular option for users. Figure 1 is an illustration of an example of a microservice architecture. Usually, web requests sent to a web server are forwarded to the various microservices behind, and they trigger a series of communications between related microservices. Since the number of web requests to the webserver represents the workload of this entire application, we name it the Primary Workload. As shown in Figure 1, these microservices include stateless microservices such as web servers and stateful microservices such as databases. There are complicated and complex communications between these microservices, for example, inter-process communications, remote invocations, or indirect communications . A webserver (MS-A) sends data to the backend database (MS-B), an example of inter-process communications. An example of remote invocations is the two-way communications between the downstream microservice (MS-C) and its upstream microservice (MS-D), and an example of indirect communications is the traffic from message consumers (MS-F and MS-G) consuming messages from a message queue (MS-E). These communication behaviors between applications in a microservice system introduce a variety of workload patterns, especially for a serverless cloud platform . Figure 1. An Illustration for a General Microservice Architecture Prediction-based Resource Management For typical resource management of an application with many microservices deployed in a Kubernetes system, it is desired to allocate the right amount of resources to all the microservices so that performance would not be suffered because of resource constraints... --- > Federator.ai realizes AIOps by utilizing operation data for ML-based predictions and intelligently orchestrating application resources. Start for FREE! - Published: 2021-12-10 - Modified: 2024-09-27 - URL: https://prophetstor.com/federator_ai/ Why Needs An AIOps Tool If your operations are facing these challenges, you need to check out our AIOps solution, Federator. ai, regardless of which phase of the digital transformation journey you are in. Complexity of Adoption & Operations To manage the patchwork of legacy and cloud technology for now and plan cloud migration for the futureTo integrate cloud-based platforms to solve business problems rather than solving the integration itselfTo adopt one dashboard to manage different services/ solutions and operations in a MultiCloud environment Increasing Waste of Cloud Resources To reduce waste on over-provisioned computing resources in cloud operationsTo identify idle resources and their correlations with certain applications and performance KPIs To evaluate the cost of different cloud providers and plan ahead for potential savings in the future Difficulty in Performance Enhancement To have ideal resource allocation for desired performance without experienced or skilled professionals involvedTo meet the dynamic demands of different applications based on continuous and accurate predictions To enable intelligent autoscaling for applications to meet the performance goals with dynamic workload demandsBenefits of Federator. ai Federator. ai, an agentless solution, integrates with the existing monitoring services and adds values to the collected operation metadata to proactively resolve operation resource issues before they become problems. With an insightful understanding of full-stack correlations (clouds, infrastructure, Kubernetes, applications) for resources, Federator. ai analyzes live time-series data to build AI-based prediction models and uses the predicted workload to provide Just-in-Time Fitted recommendations for application resources. Together with intelligent auto-scaling, Federator. ai achieves... --- > With autoscaling recommendation from Federator.ai, users can experience better performance in a more cost-efficient way for upstream web services on K8s. - Published: 2021-12-02 - Modified: 2023-07-05 - URL: https://prophetstor.com/integrations/nginx/ Federator. ai® & NGINX Integration NGINX Ingress Controller is a traffic management solution for cloud‑native apps in Kubernetes and containerized environments. With autoscaling recommendations from Federator. ai, users can experience better performance in a more cost-efficient way for upstream web services. Diagram∣The Federator. ai/NGINX integration workflow 1. Collect workloads and KPI from Ingress Controller. 2. Modeling and Machine-Learning-based predictions for workloads. 3. Apply Federator. ai recommendations for autoscaling. Benefits from Federator. ai® Effective workload predictions Federator. ai uses HTTP request rate of the Ingression Controller and target KPI metrics such as average response time and HTTP response error rate as the key metrics for autoscaling upstream web services. Predictions of HTTP request rate give a more accurate indication of real workloads for the upstream web services. Cost-effective application deployments Federator. ai integrates the workload metrics, workload predictions, and application KPI in deciding the right number of replicas and achieves more cost-effective application deployments. Achieving desired performance Without guessing or experimenting on what metric threshold to set in Kubernetes native HPA, Federator. ai achieves better use of resources for desired performance automatically. Dashboard∣Federator. ai dashboard for Ingress Upstream Services Start Federator. ai for free today and benefit from the values of machine-learning for your NGINX application. --- > The Head of Business Development and Head of Partner Ecosystems at AWS, the Director of Marketing/Channel/Storage business at Sun Microsystems, VP at EMC, Managing Director at Bluecoat, President at Data Domain, Country Manager at Violin Memory, and Managing Director at Nutanix. - Published: 2021-11-30 - Modified: 2022-10-18 - URL: https://prophetstor.com/team/ahim-kho/ Ahim Kho Linkedin-in Chief Strategy Officer Prior to joining ProphetStor, Ahim held multiple positions at AWS as the Head of Business Development and Head of Partner Ecosystems, covering Hong Kong/Macau and Taiwan. At AWS, Ahim participated in the launch of the AWS HK region, established the first AWS AIOT Global Certification Lab in Taipei, helped the Taipei government become the largest Open Data Implementation city in Asia, and established the first AWS Smart City Solution Hub in HK. During his 25-year career, Ahim was a services engineer at Ricoh, a systems engineer at IBM, and the Director of Marketing/Channel/Storage business at Sun Microsystems. He also served as VP at EMC, Managing Director at Bluecoat, President at Data Domain, Country Manager at Violin Memory, and Managing Director at Nutanix. Ahim has a track record of helping fledging technology companies grow their businesses from the ground up to having sizable revenue within 2-3 years. At the same time, he successfully helped numerous partners get listed on their local stock markets with his wide area of technical knowledge about mechanical, electronic, telecommunication, networking, network security, software development, enterprise systems management & recovery, digital transformation, and cloud economy. These experiences have successfully led him to develop competitive selling strategies, marketing, channel management, and business development for these companies. Meet Our Team --- > Utilizing Machine Learning technology for predictions and analysis, Federator.ai achieves much better performance with much fewer resources by AI autoscaling. - Published: 2021-11-10 - Modified: 2024-08-28 - URL: https://prophetstor.com/integrations/kafka-consumer-autoscaling/ Federator. ai® & Kafka Integration Apache Kafka, an open-source distributed event streaming platform, is primarily used to build a real-time streaming platform that handles trillions of constant influx of data a day and processes the data pipelines and applications that adapt to the fluctuation of data streams. By using Machine Learning technologies for predictions and analysis, Federator. ai achieves much better performance (reduced latency) with much fewer resources (reduced number of Kafka consumers) and makes implementing autoscaling of Kafka consumers simple and straightforward. Diagram∣The Federator. ai/Kafka integration workflow 1. Workload indicators based on message production rate and consumer lag from Kafka. 2. Modeling and Machine-Learning-based predictions for workloads. 3. Apply Federator. ai recommendations for the right numbers of consumer replicas. Benefits from Federator. ai® Effective workload predictions Federator. ai uses message production rate of a Kafka topic and target KPI metrics such as the desired latency as the key metrics for autoscaling Kafka consumers. Predictions of message production rate give a more accurate indication of real workloads for Kafka consumers. Cost-effective application deployments Federator. ai integrates the workload metrics, workload predictions, and application KPI in deciding the right number of replicas and achieves more cost-effective application deployments. Achieving desired performance Without guessing or experimenting on what metric threshold to set in Kubernetes native HPA, Federator. ai achieves better use of resources for desired performance automatically. Dashboard∣Federator. ai dashboard for Kafka Consumers Video∣A presentation in Kafka Summit on why intelligent autoscaling is better than Kubernetes native HPA Video∣How to configure an... --- > With the integration of Prometheus, Federator.ai analyzes the application and workload metrics and offers the workload predictions and resource recommendations. - Published: 2021-11-05 - Modified: 2024-09-02 - URL: https://prophetstor.com/integrations/prometheus/ Federator. ai® & Prometheus Integration Prometheus, 100% open source and community-driven, is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts when specified conditions are observed. With the integration of Prometheus, Federator. ai collects the application workload metrics from Prometheus monitoring service. Federator. ai analyzes the applications and workload metrics and provides the workload predictions and resource recommendations. Users can easily manage cluster and applications from Federator. ai web console. Diagram∣The Federator. ai/Prometheus integration workflow 1. Data Adapter queries applications metrics from Prometheus. 2. KEDA pulls recommendations from Federator. ai. 3. KEDA HPA autoscales applications based on recommendations. 4. Federator. ai Dashboard displays workload metrics and predictions/ recommendations. Video∣The features and the GUI (graphical user interface) of Federator. aihttps://youtu. be/AeSH8yGGA3QStart Federator. ai for free today and benefit from the values of machine-learning for your Prometheus monitoring environments. --- > With the integration of Sysdig, Federator.ai analyzes the applications and workload metrics and provides the workload predictions and resource recommendations. - Published: 2021-11-04 - Modified: 2023-07-05 - URL: https://prophetstor.com/integrations/sysdig/ Federator. ai® & Sysdig Integration Sysdig inspects every aspect of your Kubernetes Clusters, from capacity to control plane, so enterprise customers have full visibility of cloud infrastructure and application deployment status, and avoid potential problems. With the integration of Sysdig, Federator. ai collects the application workload metrics from Sysdig Monitor service. Federator. ai analyzes the applications and workload metrics and provides the workload predictions and resource recommendations. Users can easily manage cluster and applications from Federator. ai web console, and with predefined custom Sysdig dashboards, Sysdig customers can manage/monitor clusters and applications all from the same single pane of glass. Diagram∣The Federator. ai/Sysdig integration workflow 1. Sysdig Agent posts application metrics to Sysdig Monitor service. 2. Data Adapter queries application metrics from Sysdig Monitor service. 3. Data Adapter exports predictions/ recommendations to Sysdig Agent. 4. Sysdig Agent forwards Federator. ai predictions/ recommendations to Sysdig Monitor service. 5. KEDA pulls recommendations from Federator. ai. 6. KEDA HPA autoscales applications based on recommendations. 7. Sysdig Monitor Dashboards display cluster/application workload predictions and resource recommendations by Federator. ai. A Single-pane-of-glass Management Console Other than using the GUI of Federator. ai, users who are familiar with Sysdig can also use the Sysdig web portal to take advantage of AI-based predictions and recommendations from Federator. ai. ProphetStor Federator. aiCluster Overview It shows future CPU and memory usage predictions and recommendations for the entire cluster and for each individual cluster node in the next 24 hours, 7 days, or 30 days. It also displays cluster node... --- > By integrating with Datadog, Federator.ai can track and predict resource usage to prevent costly over-provisioning or performance-impacting under-provisioning. - Published: 2021-11-03 - Modified: 2024-09-02 - URL: https://prophetstor.com/integrations/datadog/ - Folder: Integrations Federator. ai® & Datadog Integration Datadog provides monitoring for servers, applications, and services. With Datadog, enterprise customers are able to monitor their application workloads and get visibility into Kubernetes clusters of any scale. By integrating with ProphetStor Federator. ai, you can track and predict the resource usages of Kubernetes containers, namespaces, and cluster nodes to make the right recommendations and prevent costly over-provisioning or performance-impacting under-provisioning. With easy integration to CI/CD pipeline, Federator. ai enables continuous optimization of containers whenever they are deployed in a Kubernetes cluster. Utilizing application workload predictions, Federator. ai auto-scales application containers at the right time and optimizes performance with the right number of container replicas through Kubernetes HPA or Datadog Watermark Pod Autoscaling (WPA). Diagram∣The Federator. ai/Datadog integration workflow 1. Datadog Agent posts workload metrics to Datadog Services. 2. Data Adapter queries workload metrics from Datadog Services. 3. Data Adapter posts the prediction/ recommendation created by Federator. ai to Datadog Services. 4. Datadog Cluster Agent gets recommendation from Datadog Services. 5. HPA autoscales applications based on recommendations. 6. Datadog Dashboards display workload metrics and prediction/recommendation by Federator. ai. A Single-pane-of-glass Management Console Other than using the GUI of Federator. ai, users who are already familiar with Datadog can also use the Datadog web portal to take advantage of AI-based predictions and recommendations from Federator. ai. There are four custom dashboards as shown below: ProphetStor Federator. ai Cluster Overview It shows future CPU and memory usage predictions and recommendations for the entire cluster and for each individual cluster... --- > Integration with existing monitoring services and Cloud platforms for fast adoption of ML-based automated solutions for optimization of cost and performance. - Published: 2021-11-03 - Modified: 2024-08-30 - URL: https://prophetstor.com/integrations/ - Folder: Integrations Federator. ai integrates with multiple monitoring services and platforms in Kubernetes and VM environments, enabling enterprises to quickly adopt this machine learning-based solution. It provides full-stack visibility, automation, and optimization for cost and performance across layers, allowing businesses to achieve AIOps and support scalable growth. Metric Data Sources Federator. ai's seamless integration with popular monitoring services in the market enables agentless installation. By utilizing existing rich sets of operational metrics, Federator. ai provides insightful full-stack analysis, resulting in precise workload predictions and well-fitted recommendations for operational optimization. kubernetes-icon-1 Kubernetes vm-icon VM Applications Federator. ai intelligent autoscaling with workload prediction ensures application performance with optimal resource allocation. kubernetes-icon-1 Kubernetes Platforms Federator. ai supports multiple platforms and public cloud services, allowing enterprises to implement their cloud adoption and migration strategies accordingly. kubernetes-icon-1 Kubernetes Red Hat OpenShift SUSE Rancher VMware Tanzu AWS Azure Google Cloud IBM Cloud vm-icon VM --- > With Federator.ai, SUSE/ Rancher can benefit from the efficiency of capacity planning, continuous optimization of resource allocation, and cost savings. - Published: 2021-10-29 - Modified: 2024-01-18 - URL: https://prophetstor.com/suse-rancher-marketplace/ What is Federator. ai® Federator. ai helps enterprises optimize cloud resources, maximize application performance, and save significant cost without excessive over-provisioning or under-provisioning of resources, meeting the service-level requirements of their applications. Enterprises often lack understanding of the resources needed to support their applications. This leads to either excessive over-provisioning or under-provisioning of resources (CPU, memory, storage). Using machine learning, Federator. ai determines the optimal cloud resources needed to support any workload on Kubernetes and helps users find the best-cost instances from cloud providers for their applications. How Federator. ai® benefits SUSE/ Rancher customers Rancher is an open-source software platform that enables organizations to run containers at scale. With Federator. ai, SUSE/ Rancher can benefit from understanding the application resource usage for better capacity planning, continuous optimization of application resource allocation and reduced deployment cost, and intelligent autoscaling that meets application performance goals without wasted resources. What is Federator. ai® Federator. ai helps enterprises optimize cloud resources, maximize application performance, and save significant cost without excessive over-provisioning or under-provisioning of resources, meeting the service-level requirements of their applications. Enterprises often lack understanding of the resources needed to support their applications. This leads to either excessive over-provisioning or under-provisioning of resources (CPU, memory, storage). Using machine learning, Federator. ai determines the optimal cloud resources needed to support any workload on Kubernetes and helps users find the best-cost instances from cloud providers for their applications. How Federator. ai® benefits SUSE/ Rancher customers Rancher is an open-source software platform that enables organizations to... --- > Federator.ai provides cost projection by workload predictions, operational savings with continuous rightsizing, and optimal migration scenarios for MultiCloud. - Published: 2021-10-13 - Modified: 2025-05-26 - URL: https://prophetstor.com/cost-management/ IT administrators struggle to predict application resource demands, making it difficult to plan and budget for cloud infrastructure costs. This leads to inevitable over-provisioning, with at least 30% of cloud spending wasted. Federator. ai, a machine learning based solution, provides not only cost analysis of clusters or VMs for a smarter MultiCloud strategy but also optimized recommendations that help utilize resources based on workload predictions. Furthermore, it offers cost comparison among major public cloud service providers and make your cloud migrations much easier. Cost Projection with Workload Predictions ML-based predictive analytics provides a forecast for capacity and recommendations for the entire cluster or individual VM. Operational Savings with Continuous Rightsizing Utilize predictive analytics for application resource demands to achieve continuous rightsizing of the applications. Migrate to Other Clouds Facilitate cloud migration decision by means of immediate cost comparisons and cluster configuration recommendations from major public clouds. Federator. ai can be easily installed on our Kubernetes clusters at Orange. Using Federator. ai, we now have the predictability of our workloads and clear visibility of the resource requirements for each of our applications. Willem BerroubacheCloud and Security Engineer at Orange See How ProphetStor Helps Orange France Watch Video See How ProphetStor Helps Orange France Watch Video Read More How Federator. ai is Helping a Leading Networking Company Improve Cloud Resource Management Case Study Cloud Cost Management with Machine Learning-based Resource Predictions (Part I) Blog How Federator. ai Optimizes Cost Savings for MultiCloud Deployments Whitepaper --- > Based on machine learning for the application-specific workload and KPI metrics, Federator.ai provides Just-in-Time Autoscaling to fit the application demands. - Published: 2021-10-13 - Modified: 2024-09-03 - URL: https://prophetstor.com/performance-optimization/ DevOps teams struggle with too many performance tuning options. Trial and error is time-consuming and unreliable for setting autoscaling thresholds, often leading to over-scaling with wasted resources or under-scaling that fails to meet performance goals during peak loads. Federator. ai uses intelligent autoscaling with application workload predictions to learn each pod's capacity and scale the number of pods at the right time. The Application-aware HPA offers a simple, cost-effective way to autoscale application containers and meet performance goals with optimal resource allocation. Machine Learning-based HPA Leverage Federator. ai’s machine-learning-based autoscaling to eliminate the need for manual tuning and experimentation with metric thresholds, ensuring optimal scaling results. Just-in-Time Autoscaling Utilize continuous, real-time workload and performance metrics to learn dynamic patterns and container capacity, enabling the scaling of the right number of replicas at the right time. Application-aware Autoscaling Automatically scale Kubernetes containers based on application-specific workload and KPI metrics, achieving autoscaling aligned with real workload demands and performance targets. Red Hat has put countless hours into curating our partner ecosystem and this includes Cloud Cost Management companies to help our customers manage their day 2 operations and onward. Companies like ProphetStor run on our Red Hat OpenShift Container Platform to provide performance, cost and efficiency management at the workload level. Cody RichardGlobal Partner Solutions Architect, Red Hat Read More A Major Telecom in Europe Automates Resource Management and Optimization on MultiCloud with ProphetStor Case Study A Smarter, Cost-efficient Way to Provision Cloud Workloads with ProphetStor Federator. ai Blog Improving Cloud-Native Application... --- > Federator.ai is an AI-based solution that helps enterprise who uses Sysdig service manage, optimize, auto-scale resources for any applications on Kubernetes. - Published: 2021-04-28 - Modified: 2023-02-23 - URL: https://prophetstor.com/sysdig-integration/ Federator. ai®  IntegrationFederator. ai integration with Sysdig to optimize application performance Sysdig Integration Federator. ai®  Integration Federator. ai integration with Sysdig to optimize application performance Sysdig Integration ProphetStor Federator. ai® ProphetStor Federator. ai is an AI-based solution that helps enterprise manage, optimize, auto-scale resources for any applications on Kubernetes. Using advanced machine learning algorithms to predict application workload, Federator. ai scales the right amount of resources at the right time for optimized application performance. AI-based workload prediction for Kafka consumers or any applications Resource recommendation based on workload prediction, application, Kubernetes and other related metrics Automatic scaling of application containers through Kubernetes Horizontal Pod Autoscaler via Sysdig extension API server. Application cost analysis estimates potential savings when following resource allocation recommendations Closed-loop automation for continuous resource optimization for applications With integration of Sysdig, Federator. ai collects the application workload metrics from Sysdig Monitor service. Federator. ai analyzes the applications and workload metrics and provides the workload predictions and resource recommendations. Users can easily manage cluster and applications from Federator. ai web console, and with predefined custom Sysdig dashboards, Sysdig customers can manage/monitor clusters and applications all from the same single pane of glass. Federator. ai® Dashboard Overview Recommended Replicas vs Current/Desired Replicas This timeseries graph shows the recommended replicas from the Federator. ai and the desired and current replicas in the system. Production vs Consumption vs Production Prediction This timeseries graph shows the Kafka message production rate and consumption rate and the production rate predicted by Federator. ai. Kafka Consumer Lag This... --- > Submit the form for a free AIOps software download. An email with information on Federator.ai installation will be sent to you. Let’s start to optimize Cloud. - Published: 2021-04-27 - Modified: 2023-10-17 - URL: https://prophetstor.com/federator-ai-trial/ hbspt. forms. create({ region: "na1", portalId: "9197010", formId: "8bd10f14-d4fd-4a41-a3a0-5aefa663944d" }); --- > Documentation for powerful AI-powered solutions for GPU and MultiCloud, including installation guides, user guides, and release notes for different versions. - Published: 2020-12-08 - Modified: 2024-08-28 - URL: https://prophetstor.com/documentation/ Federator. ai GPU Booster Federator. ai Documentation of Federator. ai GPU Booster Installation Guide Federator. ai GPU Booster 5. 2. 0 Installation Guide User Guide Federator. ai GPU Booster 5. 2. 1 – User Guide Federator. ai GPU Booster 5. 2. 0 – User Guide Documentation of Federator. ai Installation Guide Federator. ai 5. 1. 5 Installation Guide by Using Helm Chart Federator. ai 5. 1 Installation Guide Federator. ai 5. 0 Installation Guide Federator. ai 4. 7. 2 Installation Guide Federator. ai 4. 6. 1 Installation Guide v1. 0 Federator. ai 4. 5. 1 Installation Guide v1. 0 Federator. ai 4. 4. 1 Installation Guide v1. 0 Federator. ai 4. 3. 1 for Datadog – Installation Guide v1. 0 Federator. ai 4. 3 for OpenShift (Marketplace) – Installation Guide v1. 3 User Guide Federator. ai 5. 1 – User Guide Federator. ai 5. 0 – User Guide Federator. ai 4. 7. 2 – User Guide Federator. ai 4. 6. 1 – User Guide Federator. ai 4. 5. 1 – User Guide Federator. ai 4. 4 – User Guide Federator. ai 4. 3 for Datadog – User Guide Federator. ai AWS IAM Role and IAM Policy Setup Guide Federator. ai Azure App Registration Setup Guide Federator. ai Google Cloud Service Account Setup Guide Release Notes Federator. ai 5. 1 Release Notes Federator. ai 5. 0 Release Notes Federator. ai 4. 7. 2 Release Notes Federator. ai 4. 6. 1 Release Notes Federator. ai 4. 5. 1 Release Notes Federator. ai... --- - Published: 2020-12-02 - Modified: 2024-09-19 - URL: https://prophetstor.com/white-papers/federator-ai-drastically-improves-cost-and-performance-of-kafka-running-on-kubernetes/ - 頁面分類: Whitepapers - Folder: Whitepapers Introduction A Kafka Stream Application reads data from a topic, performs calculations and transformations, and then writes the result back to another topic. To read from a topic, it creates a consumer. Kafka has become a standard tool for managing a high-load streaming system. However, it lacks built-in mechanisms for dynamic cluster capacity planning and scaling strategies. Scaling the application involves running more consumers. Typically, to optimize the consumer processing rates, users assign the same number of consumers as there are partitions for related topics. However, this 'over-provisioning' approach can lead to unnecessary resource waste. To address this, some efforts have been made to use Kubernetes Horizontal Pod Autoscaler (HPA) to manage consumer groups in a Kafka cluster , with the hope that the autoscaler can dynamically allocate the right amount of resources at the right time, improving resource utilization. However, there are some drawbacks to using Kubernetes HPA: Limitations of Kubernetes HPA: Kubernetes HPA combines recommendations (calculating desired replicas) with executions (adjusting the number of replicas) via the HPA controller. As operator-based applications become more prevalent in Kubernetes clusters, Kubernetes HPA is less suitable for auto-scaling these applications. In some cases, users may prefer to receive only scaling recommendations and handle executions separately through custom methods. Challenges with Metrics: If the metrics used to calculate the desired number of replicas are not chosen carefully, performance can suffer. Users need to carefully select appropriate metrics, often through trial and error, to avoid negative impacts on performance. In this article, we... --- > Federator.ai tackles how to adjust microservices to improve the application KPIs with ML-based Multi-Layer correlation, prediction, and application-aware HPA. - Published: 2020-11-13 - Modified: 2024-03-18 - URL: https://prophetstor.com/white-papers/improving-cloud-native-application-kpis-with-multi-layer-correlation-and-prediction/ - 頁面分類: Whitepapers - Folder: Whitepapers Introduction Kubernetes enables the deployment of a complex system, called the main application here, by integrating several microservices in many innovative fashions. The main application can be an online retail shopping website or a web service that supports airline ticket reservations. For example, one can build a full-fledged online shopping website by combining several microservices such as NGINX as front-end servers, Tomcat as web services, Postgres Database for storage. One can further integrate Logstash and Elasticsearch to enhance the user experience with advanced analytics. Each of the microservices can be updated and scaled independently to meet the changing demands on features and scales. One or more metrics, called main application Key Performance Indicators (KPIs), are monitored carefully to gauge the performance of the main application and to ensure the proper operation of the system. Among those KPIs, some could be used as an indicator of the workload of the main application, and others are used to measure the performance of the main application. These KPIs can be influenced by the number of microservice PODs and resources like CPU and memory allocated to each of the microservices. Finding the right amount of resources and the right number of pods of these microservices to achieve the target performance goal of the main application is a complicated task. It is most likely done by a trial-and-error approach with a lot of manual processes. Federator. ai, an AIOps platform for Kubernetes/OpenShift clusters from ProphetStor, tackles the challenge of how to adjust microservices to improve... --- > Organizations waste 30 percent of cloud spend. It results from the lack of visibility and capability of cloud resources. The most cost-effective way for AIOps… - Published: 2020-11-10 - Modified: 2024-09-19 - URL: https://prophetstor.com/white-papers/how-federator-ai-optimizes-cost-savings-for-multicloud-deployments/ - 頁面分類: Whitepapers Wastes of cloud spend With the public and hybrid cloud adoption rapidly growing, enterprises and organizations continue to increase their spending on cloud infrastructure. However, most of the increased spending is not turning into business revenue. In the recent survey of 2020 State of the Cloud Report by Flexera over 750 technical professionals worldwide, respondents self-estimate organizations waste 30 percent of cloud spend. Flexera has found that actual waste is 35 percent or even higher. The significant wasted cloud spend drives organizations to focus on cost savings. About 73 percent of the organizations surveyed plan to optimize their existing cloud resources to achieve better cost savings. However, most organizations struggle to handle the growing cloud spend due to a lack of resources or expertise . Let’s do some calculations on the 35 percent waste of cloud spend. Gartner recently predicted that the Cloud System Infrastructure Services (IaaS) spending will reach $50 billion in 2020, an increase of 13% from 2019. That means about $17. 5 billion of wasted cloud spending in 2020 alone, and this number will keep increasing, given the growth of the cloud. Another study from ParkMyCloud also arrives at a similar conclusion that the Wasted Cloud Spend would exceed $17. 6 Billion in 2020. Just as the title of article by Larry Dignan (Editor in Chief of ZDNet), cloud cost control is becoming a leading issue for businesses. Figure 1. Percentage of Cloud Spend Wasted Table 1. Worldwide Public Cloud Service Revenue Forecast (Millions of U. S.... --- - Published: 2020-11-05 - Modified: 2024-09-19 - URL: https://prophetstor.com/white-papers/why-horizontal-pod-autoscaling-in-kubernetes-needs-to-be-application-aware/ - 頁面分類: Whitepapers - Folder: Whitepapers Introduction The workloads running in Kubernetes clusters are characterized by their respective Key Performance Indicators (KPIs). To meet diverse, application-specific KPI objectives, Kubernetes implements a generic framework known as Horizontal Pod Autoscaling (HPA), which scales up and down the number of pods with the same characteristics. The HPA controller can perform autoscaling using either standard metrics like CPU utilization or custom metrics based on the following formula. At first glance, this approach seems reasonable. However, this whitepaper shows that such a method is too simplistic for many applications, potentially leading to resource wastage or decreased performance. It has been observed that Application KPIs are not necessarily directly related to Pods’ CPU and memory utilization. Scaling the number of Pods based on a single, generic metric may not result in optimal KPI outcomes for the underlying applications. Multiple metrics may be necessary for many applications, such as Kafka consumer workloads to determine the appropriate number of consumers required to process Kafka broker messages without introducing excessive processing latency. In this context, message processing latency could serve as the KPI for the application. More importantly, most workloads exhibit predictable behaviors. Leveraging these behaviors can distinguish an application-aware HPA solution from other naive approaches. We also demonstrate that by utilizing application-specific metrics and machine learning-based workload prediction, ProphetStor’s application-aware HPA achieves an over 40% reduction in the number of required replicas compared to a standard CPU-utilization-based HPA. Kubernetes Scaling with Application-Awareness In Kubernetes, scaling criteria can be based on metrics such as CPU... --- - Published: 2020-08-27 - Modified: 2024-06-26 - URL: https://prophetstor.com/press-releases-2/press-releases/ Press Releases 2024 2020 2023 2019 2022 2018 2021 2017 2024 2023 2022 2021 2020 2019 2018 2017 --- > It includes ProphetStor Privacy Statement, which explains how ProphetStor collects/ uses/ discloses your information, and End User License Agreement (EULA). - Published: 2020-08-19 - Modified: 2023-11-20 - URL: https://prophetstor.com/legal/ Privacy Statement Last Updated: December 18, 2019ProphetStor Data Services, Inc. and its affiliated companies and subsidiaries (collectively, “ProphetStor,” “we,” us,” or “our”) respect your privacy. This Privacy Statement explains how ProphetStor collects, uses, and discloses your information. The Privacy Statement applies to all services and products, except those products that have a separate Privacy Statement. Where applicable, you consent to the use of your information as described in this Privacy Statement each time you use our products or services or... Read more EULA Last Updated: November 20, 2023This End User License Agreement (“EULA”) is a legal contract between you, eitheras an individual or a single entity (“you”), and ProphetStor Data Services, Inc. , its subsidiaries and affiliates (collectively, “ProphetStor”), governing your use of the software, services, and associated online or electronic documentation published, distributed or otherwise made available by ProphetStor (this software, services, and documentation, and any applicable updates provided by ProphetStor, collectively referred to as the “Software”), and if applicable, your use of Software designed for application with ProphetStor hardware devices and products... Read more --- - Published: 2020-08-19 - Modified: 2023-11-20 - URL: https://prophetstor.com/legal/eula-legal/ ProphetStor End User License Agreement Last Updated: November 20, 2023 This End User License Agreement (“EULA”) is a legal contract between you, eitheras an individual or a single entity (“you”), and ProphetStor Data Services, Inc. , its subsidiaries and affiliates (collectively, “ProphetStor”), governing your use of the software, services, and associated online or electronic documentation published, distributed or otherwise made available by ProphetStor (this software, services, and documentation, and any applicable updates provided by ProphetStor, collectively referred to as the “Software”), and if applicable, your use of Software designed for application with ProphetStor hardware devices and products (“ProphetStor Devices”). If, however, ProphetStor software or services are accompanied by a separate license agreement, the terms of that separate license agreement will apply to your use of the applicable ProphetStor software or services. BY INSTALLING, ACTIVATING, COPYING OR OTHERWISE USING THE SOFTWARE, YOU AGREE TO BE BOUND BY THE TERMS OF THIS EULA, WHICH ARE CONDITIONS TO PROPHETSTOR’S LICENSE GRANT TO YOU PURSUANT TO THIS EULA, AND THE PROPHETSTOR PRIVACY POLICY, AS INCORPORATED BY REFERENCE IN SECTION 5 BELOW. IF YOU DO NOT AGREE TO THE TERMS OF THIS EULA AND THE PROPHETSTOR PRIVACY POLICY, DO NOT INSTALL, ACTIVATE, COPY, OR USE THE SOFTWARE. YOU REPRESENT AND WARRANT THAT YOU HAVE THE RIGHT, AUTHORITY, AND CAPACITY TO ACCEPT AND AGREE TO THIS EULA ON BEHALF OF YOURSELF OR THE ENTITY YOU REPRESENT. YOU REPRESENT THAT YOU ARE OF SUFFICIENT LEGAL AGE IN YOUR JURISDICTION OR RESIDENCE TO USE OR ACCESS THE SOFTWARE... --- > Announcements of new partnerships in the industry, a new release of the company’s flagship AIOps solution Federator.ai, and new clients adopting Federator.ai. - Published: 2020-08-19 - Modified: 2024-01-22 - URL: https://prophetstor.com/press-releases-2/ 8 6 月, 2023 Juniper Mist Leverages ProphetStor’s Federator. ai to Power Cloud Automation and Optimization Learn more 15 2 月, 2023 Federator. ai Solution Granted a Patent for Application-aware, Resilient, and Optimized IT/Cloud Operations Learn more 15 7 月, 2022 Industry-Leading Chunghwa Telecom Adopts ProphetStor Federator. ai for Green IT and Intelligent Continuous Cloud Operations Learn more 21 4 月, 2022 ProphetStor Partners with Nextlink Technology to Exponentially Expand Managed Service Providers’ Businesses and Achieve Customer Obsession Learn more 11 2 月, 2022 ProphetStor Honors Sales and Technology Partner Evanston Technology Partners and Its CEO Emmanuel Jackson in Celebrating Black History Month Learn more 27 1 月, 2022 ProphetStor Releases Federator. ai 5. 0 for Planning, Automation, and Optimization of The Next Phase Full-Scale Business-Focused Cloud Operations Learn more Show More --- > Chen was the Vice President and General Manager of Asia Pacific Operations at FalconStor Software Inc. He holds a Ph.D. in computer and information science from Ohio State University and a B.S. in electrical engineering from National Taiwan University. - Published: 2020-08-18 - Modified: 2022-10-18 - URL: https://prophetstor.com/team/eric-chen/ Eric Chen Linkedin-in Co-Founder, Chairman and CEOEric Chen is the Founder and CEO of ProphetStor Data Services, Inc. Before starting ProphetStor, he was the Co-Founder, Vice President, and General Manager of Asia Pacific Operations at FalconStor Software, Inc. , which was listed on NASDAQ in 2001. Dr. Chen holds a Ph. D. in Computer and Information Science from The Ohio State University and a B. S. in Electrical Engineering from National Taiwan University. Meet Our Team --- > Sheu holds a Ph.D. in computer and information science from Ohio State University and a B.S. in computer science and information engineering from National Taiwan University. - Published: 2020-08-18 - Modified: 2022-10-18 - URL: https://prophetstor.com/team/ming-sheu/ Ming Sheu Linkedin-in Executive Vice President of ProductsMing Sheu is a Serial Entrepreneur. Before ProphetStor, he served as the VP of Cloud Engineering at Ruckus, listed in NYSE and acquired by Brocade. He led a global team building the next-generation cloud-native network management applications, serving and transforming worldwide operations. Dr. Sheu holds a Ph. D. in Computer and Information Science from The Ohio State University and a B. S. in Computer Science and Information Engineering from National Taiwan University. Meet Our Team --- - Published: 2020-08-17 - Modified: 2022-08-19 - URL: https://prophetstor.com/kubernetes-monitoring-multicloud-hybrid-cloud-plaftorm/datadog/ Federator. ai® & Datadog Integration Datadog provides monitoring for servers, applications, and services. With Datadog, enterprise customers are able to monitor their application workloads and get visibility into Kubernetes clusters of any scale. Federator. ai integration with Datadog aggregates metrics and events and provides resource prediction/recommendation for Kubernetes deployments and application-aware acceleration and optimization for Kafka. The following diagram illustrates the Federator. ai/Datadog integration workflow. 1. Datadog Agent posts workload metrics to Datadog Services 2. Data-Adapter queries workload metrics from Datadog Services 3. Data-Adapter posts the Prediction/Recommendation created by Federator. ai to Datadog Services 4. Datadog Cluster Agent gets Prediction/Recommendation from Datadog Services 5. WPA applies Recommendation to applications 6. Datadog Dashboard displays workload metrics and Prediction/Recommendation by Federator. ai Using Kafka as an example, the Datadog Agent monitors and collects many different types of Kafka metrics, including resources (e. g. , CPU, memory) utilization and Kafka workload and performance metrics (e. g. , message queue offset/length, consumer lags). With integration of ProphetStor Federator. ai, Kafka message production/consumption rate is continuously collected from Datadog by Federator. ai’s data-adapter and analyzed by the AI engine of Federator. ai. Federator. ai uses advanced machine learning algorithms to predict the Kafka message production rate. Based on the prediction of message production rate, Federator. ai works with WPA to automatically scale Kafka consumer replicas to handle the increased or decreased workload. Read More Federator. ai solution for auto-scaling on K8S with Datadog Federator. ai User Guide Federator. ai Installation and Configuration Guide --- > Federator.ai integration with Datadog to optimize application performance on Datadog dashboard and be available on Datadog Marketplace - Published: 2020-08-17 - Modified: 2023-02-23 - URL: https://prophetstor.com/datadog-integration/ Federator. ai®  Integration Federator. ai integration with Datadog to optimize application performance Datadog Integration (A Datadog account is required for connecting and using Datadog. If you don’t have an account, visit the Datadog website and sign up for a free trial account. If you already have a Datadog account, please visit Datadog Marketplace to enjoy your free trial. ) Federator. ai®  Integration Federator. ai integration with Datadog to optimize application performance Datadog Integration (A Datadog account is required for connecting and using Datadog. If you don’t have an account, visit the Datadog website and sign up for a free trial account. If you already have a Datadog account, please visit Datadog Marketplace to enjoy your free trial. ) ProphetStor Federator. ai® ProphetStor Federator. ai is an AI-based solution that helps enterprise manage, optimize, auto-scale resources for any applications on Kubernetes. Using advanced machine learning algorithms to predict application workload, Federator. ai scales the right amount of resources at the right time for optimized application performance. AI-based workload prediction for Kafka or any applications Resource recommendation based on workload prediction, application, Kubernetes and other related metrics Automatic scaling of application containers through Datadog Watermark Pod Autoscaler (WPA) With integration of ProphetStor Federator. ai, users can easily track the Kafka message production/consumption rate, as well as the prediction of message production rate from Federator. ai dashboard. Based on the prediction or message production rate, Federator. ai automatically scales Kafka consumer replicas to handle the workload. This can be visualized from Federator. ai dashboard where... --- > Based in Milpitas, CA, we specialize in IT/Cloud efficiency and GPU management, delivering advanced, resilient solutions with patented AI engines. - Published: 2020-08-17 - Modified: 2024-12-24 - URL: https://prophetstor.com/ Federator. ai GPU Booster® and Federator. ai® AI-Powered Resource Optimization for GPU and MultiCloud Operations Full-stack visibility, resilient operations, ESG-friendly, and continuous optimization Request Demo Operation Simplicity Offers a holistic view of available and used compute resources, combined with workload-pattern-aware insights, to enable efficient resource planning Performance Resilience Uses patented AI-based analytics to predict workload dynamics, accelerating applications with Just-in-Time Fitted compute resources as needed Resource Efficiency Tackles MultiTenant application workloads with ingenious resource configuration, maximizing resource efficiency while reducing carbon emissions Holistic Visibility, Application-Aware Insights, and Multi-Layer Correlation Understanding Federator. ai GPU Booster Federator. ai Maximizing GPU utilization for AI workloads and reducing training execution time by half to achieve efficiency and ESG goals Simplifying the complexity of resource management and continuously optimizing operational costs and performance Learn More Watch Demo Video Learn More Watch Demo Video Holistic Visibility, Application-Aware Insights, and Multi-Layer Correlation Understanding Federator. ai GPU Booster Maximizing GPU utilization for AI workloads and reducing training execution time by half to achieve efficiency and ESG goals Learn More Watch Demo Video Federator. ai Simplifying the complexity of resource management and continuously optimizing operational costs and performance Learn More Watch Demo Video Testimonials Chris Wright CTO of Red Hat An example of a partner who is doing incredible work in the AIOps space is ProphetStor. Their solutions are being built on OpenShift and enhance its scaling and scheduling capabilities. ProphetStor and AIOps help operation teams predict and optimize workloads and resources in your cluster. Cody Richard Global Partner... --- --- ## Posts > ProphetStor's patented AI interactive dashboard redefines infrastructure management with real-time insights, dynamic workflows, and seamless human-AI synergy. - Published: 2024-12-23 - Modified: 2024-12-24 - URL: https://prophetstor.com/2024/12/23/patent-for-ai-powered-interactive-dashboard/ - Categories: Press Releases - Tags: Agentic, AI, Analytic, Cloud, DataCenters, Efficiency, GPU, Innovation, InteractiveDashboard, LLM-Powered, Predictive, Prescriptive, ProphetStor, SmartInterface, USAPatent Milpitas, CA, Dec. 24, 2024 — ProphetStor Data Services, Inc. , a global leader in AI-driven analytics and intelligent infrastructure solutions, proudly announces the issuance of a patent for its innovative “System and Method for Providing Analytics and Intelligent Question-Answering via Interactive Dashboard. ” The patented system reimagines infrastructure management by introducing an innovative conversational interface that surpasses traditional dashboard capabilities. At its core, this platform is designed to deliver agentic orchestration—a methodology that dynamically optimizes workflows and coordinates intelligent agents to execute tasks seamlessly. By extending the functionalities of the original interactive dashboard, this approach introduces greater flexibility, adaptability, and operational efficiency. Central to this transformation is the integration of advanced Large Language Models (LLMs), which enable the system to understand user intent and generate workflows dynamically. Unlike static dashboards, which rely on predefined functionalities, the patented system adapts to real-time user inputs, evolving requirements, and real-time conditions. It serves as a decision-making hub that unites human and AI agents, enhancing both collaboration and autonomy. Eric Chen, CEO of ProphetStor Data Services, Inc. , stated, “Without the capability to answer users’ questions, a dashboard is little more than a poster on a wall. Our technology turns dashboards into dynamic decision-making platforms, allowing users to discover fresh insights in previously impossible ways. ” Unlike conventional dashboards locked into static preset designs, ProphetStor’s LLM-powered solution adapts to user queries on the fly. It also resolves the performance pitfalls of overly complex dashboards with 30 filters, 100 sheets, or excessive calculations that... --- > ProphetStor Federator.ai GPU Booster optimizes GPU resources on Kubernetes with patented algorithms. Perfect for businesses using high-end NVIDIA GPUs, it streamlines GPU management, especially for MultiTenant AI model training. Maximize GPU utilization, boost training throughput, and keep your AI initiatives ahead with Federator.ai GPU Booster. - Published: 2024-06-26 - Modified: 2024-06-26 - URL: https://prophetstor.com/2024/06/26/federator-ai-gpu-booster-feature-demo/ - Categories: Intro/Demo Videos - Tags: AI, ApplicationAware, DataCenters, DevOps, GPU, GreenIT, Kubernetes, Optimization, ResourceManagement ProphetStor Federator. ai GPU Booster Feature Demo ProphetStor Federator. ai GPU Booster is a cutting-edge solution designed to optimize GPU resources on Kubernetes platforms using patented algorithms. Ideal for businesses with high-end NVIDIA GPUs, it streamlines GPU management and enhancement, particularly for MultiTenant AI model training. Federator. ai GPU Booster maximizes GPU utilization, increasing training throughput and keeping your AI initiatives ahead of the curve. For more details: https://prophetstor. com/federator-ai-gpu-booster/#Federator. ai, #GPU, #LLM, #Kubernetes, #MultiTenant, #Sustainability, #NVIDIA Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > ProphetStor has announced a reseller partnership with TOMORROW NET, a top Supermicro reseller, to transform GPU server use and sustainable computing in Japan and Korea. - Published: 2024-05-30 - Modified: 2024-05-30 - URL: https://prophetstor.com/2024/05/30/prophetstor-and-tomorrow-net-build-a-reseller-partnership/ - Categories: Press Releases - Tags: ApplicationAware, CostOptimization, DataCenters, Efficiency, Gartner, GreenIT, MachineLearning, MultiLayerCorrelation, Optimization, ResourceManagement, Sustainability Milpitas, CA, May 30, 2024 — ProphetStor Data Services, Inc. , the world's first AI-driven Cloud and GPU operation and infrastructure optimization solution provider, is thrilled to announce its unique reseller partnership with TOMORROW NET Co. ,Ltd (TOMORROW NET hereafter). , the top reseller of Supermicro in Japan. This partnership is not just about deploying and operating large language models across Japan and Korea; it's about revolutionizing the efficient utilization of GPU servers and sustainable computing solutions. This collaboration will create ripples in the region's hardware and software AI industry, marking a significant step towards efficient and effective AI deployment. Under this partnership, TOMORROW NET will aim to resell Federator. ai GPU Booster from ProphetStor, an innovative solution targeting improving GPU servers using AI model training and inferencing for efficiency and effectiveness. This relationship is, therefore, going to shape the hardware and software AI scenes in the region, building on the solid framework of TOMORROW NET service and solution delivery to easily make the complex surrounding hardware and software setup and upkeep for AI developers. This will significantly reduce the time and effort required for AI developers to set up and maintain their infrastructure, allowing them to focus more on their core tasks. “This partnership is a game-changer, poised to transform and cost-effectively realize AI deployments in Asia. We are thrilled to collaborate with TOMORROW NET, paving the way for a more integrated and cost-effective approach to businesses harnessing the power of AI, free from the usual complexities of large-scale... --- > ProphetStor received the world's 1st patent for Spatial and Temporal Optimization of GPU Utilization, a pioneering predictive analytics algorithm for AI/ML training. - Published: 2024-05-23 - Modified: 2024-05-23 - URL: https://prophetstor.com/2024/05/23/worlds-first-patent-for-spatial-and-temporal-gpu-optimization/ - Categories: Press Releases - Tags: AI, ApplicationAware, CostOptimization, DataCenters, Efficiency, GPU, GreenIT, MachineLearning, Optimization, ResourceManagement, Sustainability, USAPatent Milpitas, CA, May 23, 2024 — ProphetStor Data Services, Inc. , a trailblazing company in the field of AI-driven Cloud and GPU optimization solutions, has achieved a significant milestone. It has been awarded the world's first patent for Spatial and Temporal Optimization of GPU Utilization, a groundbreaking technology that propels ProphetStor to the forefront of AI and GPU optimization. This patent is a testament to our unique approach and our commitment to enhancing GPU resource utilization. This patent represents a significant leap in GPU technology, with a focus on improving spatial and temporal efficiencies in GPU use. By leveraging application behavior-based insights, it enhances resource usage efficiency through multidimensional predictive analytics. This means it can forecast AI workload resource demands, manage GPU resource capacity and partitions, and adapt their dynamic states over time. The result is the optimal use of GPU resources, which translates to a substantial reduction in computation time and energy consumption. This innovation paves the way for more sustainable and cost-effective AI deployments, a crucial consideration for organizations looking to harness the power of AI. "With a patent such as this, we see further evidence of ProphetStor’s commitment to innovation and excellent AI and GPU optimization," said Eric Chen, CEO of ProphetStor. "It is with game-changing technologies like this that we are setting new benchmarks in GPU efficiency and contributing toward broader sustainability and environmental goals. Our progress at the infrastructure level will enable organizations to deploy AI models more efficiently and effectively within the next wave... --- > ProphetStor is excited to announce the grant of US Patent No. 11579933 entitled "Method for Establishing System Resource Prediction and Resource Management Model through Multi-layer Correlations." - Published: 2023-02-15 - Modified: 2024-01-12 - URL: https://prophetstor.com/2023/02/15/federator-ai-solution-granted-patent-for-application-aware-resilient-and-optimized-it-cloud-operations/ - Categories: Press Releases - Tags: ApplicationAware, CostOptimization, DataCenters, Efficiency, Gartner, GreenIT, MachineLearning, MultiLayerCorrelation, Optimization, ResourceManagement, Sustainability MILPITAS, CA, February 15, 2023 — ProphetStor, a leading provider of innovative IT and cloud resource management solutions, is pleased to announce the award of US Patent No. 11579933 for "Method for Establishing System Resource Prediction and Resource Management Model through Multi-layer Correlations. " This patent marks a significant step forward for ProphetStor's Federator. ai, which provides unique application-aware resource planning and optimization capabilities for enterprise and data center IT/Cloud Operations. Federator. ai can predict application workload and build correlation models with resources using patented multi-layer correlation technology and machine learning. This enables just-in-time resource orchestration and allocation. This method ensures that application resilience is maintained while operating costs are reduced. Furthermore, this solution may be computationally feasible while meeting corporate/application KPIs. Federator. ai differentiates itself from other IT and cloud resource management solutions by providing unique application insight, resource planning, and optimization capabilities. Federator. ai's application-aware approach goes beyond the standard resource optimization offered by other solutions, making it a top choice for organizations looking to reduce their carbon footprint and optimize operations through proper resource allocation, whether using on-premises or cloud computing resources. Furthermore, Federator. ai is simple to integrate into existing data center infrastructure, making it a cost-effective and efficient solution for increasing energy efficiency. This novel approach to using predictive and prescriptive analytics for resource management is consistent with the Gartner 2023 technological trend, Applied Observability in the Optimization theme. Furthermore, Federator. ai's just-in-time resource orchestration and allocation capabilities assist customers seeking Green IT and Cost... --- > Federator.ai helps achieve the balance of maximizing both the revenue for MSP and the cost savings for its end-users and earn more upsell opportunities for MSP. - Published: 2022-08-19 - Modified: 2024-06-26 - URL: https://prophetstor.com/2022/08/19/win-win-sales-strategy-for-msp-and-end-users/ - Categories: Intro/Demo Videos - Tags: AI, AIOps, CloudInstance, Kubernetes, MachineLearning, MSP How Can We Help An MSP/ Reseller Increase Revenue in A Strategic Way? With the help of ProphetStor's MSP Operation Recommender, an MSP not only can formulate its convincing sales strategy for Reserved Instances to achieve its revenue growth and cost optimization for its end-user but can also offer value-added consulting services to get upsell opportunities and gain customer loyalty.  Eventually, a win-win scenario proposed by Federator. ai benefits both sides. Please have a look at the video below and check out one of ProphetStor's solutions about how we help an MSP produce a sound and robust sales strategy. #Federator. ai, #MSP, #CloudInstance , #Kubernetes, #ProphetStor, #MachineLearning, #AI, #AIOps Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Chunghwa Telecom (CHT) has adopted ProphetStor Federator.ai in reducing idle resources in VM clusters and achieving both cost savings and Green IT objectives. - Published: 2022-07-15 - Modified: 2024-01-15 - URL: https://prophetstor.com/2022/07/15/cht-adopts-federator-ai-for-green-it-and-cloud-operations/ - Categories: Press Releases - Tags: AI, AIOps, ApplicationAware, Datadog, DevOps, DevSecOps, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, SUSE, Sysdig MILPITAS, CA, July 15, 2022 — ProphetStor Data Services, Inc. today announced that Chunghwa Telcom (CHT), the largest telecoms company in Taiwan, has adopted ProphetStor Federator. ai in reducing idle resources in VM clusters and achieving both cost savings and Green IT objectives. Federator. ai is an IT Operations (AIOps) platform that understands the operation metadata and metrics, performs workload dynamics predictions, and recommends the Just-in-Time Fitted resources for applications. Furthermore, it provides intelligence for orchestrating Kubernetes container resources on virtual machines (VM) or bare metal. Chunghwa Telecom deploys numerous VMs in its data centers for various mission-critical applications. Maintaining the resilient operation of these VMs while identifying opportunities to reduce wasteful resources is one of the critical operational challenges. Rightsizing the resources allocated to the VMs not only provides a roadmap for cost savings but also contributes to the infrastructure's sustainability goals, allowing the company to fulfill its commitment to Environmental, Social, and Governance (ESG). Traditional VM monitoring tools only provide passive resource usage without proactive recommendations based on the predictions of application workloads and multi-layer designs. Federator. ai uses ML-based technology for dynamic workload predictions that accurately forecast resource usage. It is continuously right-sizing the VM resources. The multi-layer operation models can be used in short-term adjustments or long-term planning. “Using Federator. ai’s ML-based resource recommendation engine allows us to provision our VM resources for operation resilience more accurately,” said Mr. Chung-Shuo Lin, Managing Director of Chunghwa Telecom Cloud System Department. “The benefits of reducing operational costs while... --- > Partnering with Nextlink, a leading managed MultiCloud solution provider in China, Taiwan, Hong Kong, and Southeast Asia, to facilitate cloud journey in APAC. - Published: 2022-04-21 - Modified: 2024-01-15 - URL: https://prophetstor.com/2022/04/21/prophetstor-partners-with-nextlink/ - Categories: Press Releases - Tags: AI, AIOps, ApplicationAware, AWS, DevOps, DevSecOps, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift MILPITAS, CA, April 21, 2022 — ProphetStor Data Services, Inc. today announced its business and technical partnership with Nextlink Technology, a leading managed MultiCloud solution provider in China, Taiwan, Hong Kong, and Southeast Asia, to help our joint customers to enjoy the cloudy journey with the needed full-stack support in application and cloud for automation, resilience, and cost. Nextlink is one of the best Managed Service Providers (MSPs) in the Asia Pacific region. Nextlink has been selected as a top global public cloud infrastructure service provider and the most promising AWS Consulting Partner in the Asia Pacific by CIO Magazine in the USA. And announced as APAC High Tech High Growth Fast 500™ by Deloitte Technology. With the mission to become the best-managed service provider to provide the unparallel support for their customers, Nextlink is constantly expanding its technical teams, developing value-add solutions that the customers will need. The agreement with Nextlink demonstrates ProphetStor’s determination to deepen and strengthen its support to AWS and MultiCloud customers in Taiwan and Hong Kong. With the help of ProphetStor’s Federator. ai platform, enterprises can easily handle the dynamic application workloads in MultiCloud. With its Deep-Learning-based solution, they can continuously optimize resource usage to support application acceleration in AWS and on-premises at the same time. Just-in-Time Fitted resources recommendations are automated. Both companies have also jointly developed solutions, with the REST APIs offered by Federator. ai, to classify workloads, leverage the intelligence created through the analysis of the multi-layer correlation of the operation metadata,... --- > It offers the visibility of cloud spending at different resource levels (clusters, cluster nodes, namespaces, applications, containers), and reduces the cost. - Published: 2022-04-13 - Modified: 2024-01-15 - URL: https://prophetstor.com/2022/04/13/cloud-cost-management-with-ml-based-resource-predictions-part-ii/ - Categories: blog - Tags: AI, ApplicationAware, GreenIT, Kubernetes, MachineLearning, OpenShift, SUSE As outlined in the Guidance Framework introduced in part one of this post, once users gain visibility of spending metrics, they must see opportunities to reduce monthly bills. Reducing Cost by Continuous Rightsizing As outlined in the Guidance Framework introduced in part one of this post, once users gain visibility of spending metrics, they must see opportunities to reduce monthly bills. Federator. ai provides the visibility of cloud spending at different resource levels (clusters, cluster nodes, namespaces, applications, containers), and it makes finding ways to reduce the cost an easier task. For example, it is well documented that most containers deployed in Kubernetes clusters use far less allocated CPU and memory resources. This indicates a huge opportunity to reduce the overall cloud cost by allocating the appropriate resources for applications. However, finding the right size of resources for applications is not straightforward. With Federtor. ai’s predictive analytics, users receive the right recommendations on resource allocation without suffering potential performance risks. An essential suggestion by the Guidance Framework when looking to reduce the cost of deployment is to understand the utilization patterns of applications and services. Users should schedule cloud services and applications based on the utilization pattern from the historical data collected. Federator. ai not only provides a resource utilization heatmap based on historical usage metrics, but it also provides a utilization heatmap that further sheds light on how resources will be consumed in the future. The utilization patterns, either daily, weekly, or monthly, give users a clear view of both when and how much resources were used and will be used. This information helps users to decide what compute instances could be reduced or shut down during... --- > Federator.ai utilizes ML technologies as a unique approach to help companies solve the cloud overspending problem, which facilitates planning for cloud budget. - Published: 2022-04-13 - Modified: 2024-01-15 - URL: https://prophetstor.com/2022/04/13/cloud-cost-management-with-ml-based-resource-predictions-part-i/ - Categories: blog - Tags: AI, ApplicationAware, GreenIT, Kubernetes, MachineLearning, OpenShift, SUSE As enterprises go through digital transformation to improve efficiency, increase values and innovation, the adoption of cloud and Kubernetes has accelerated. Cloud Cost Management with ML-based Resource Predictions As enterprises go through digital transformation to improve efficiency, increase values and innovation, the adoption of cloud and Kubernetes has accelerated. However, there are many challenges. One of the major concerns of moving applications and services to the cloud is the cost. Managing cloud costs has become a challenging task for businesses and organizations. Gartner published a report on this topic and proposed a well-defined framework for managing and optimizing the costs of public cloud services . Among the key findings in this report is that most organizations are not prepared to profit from the savings opportunity of efficient use of cloud services and are likely to overspend. The report lists a series of recommendations and a Guidance Framework to manage cloud spending on an ongoing basis. Five distinct areas are defined by the framework: Plan, Track, Reduce, Optimize and Evolve. It provides a logical flow on developing and implementing capabilities in managing cloud spending. ProphetStor’s Federator. ai utilizes machine-learning technologies as a unique approach to help organizations solve the cloud overspending problem. In this article, we demonstrate how Federator. ai’s solution implements many of the recommendations suggested by Gartner’s Guidance Framework that can benefit customers using SUSE Rancher-managed clusters. Mainly, with the ability to forecast the resource usages based on the past operational metrics, Federator. ai makes use of the predicted resource usage in cost/budget planning, tracking of both past usages and predicted future usages, reducing the cost of applications by right-sizing the... --- > ProphetStor Federator.ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for the applications on Kubernetes. - Published: 2022-03-02 - Modified: 2024-06-26 - URL: https://prophetstor.com/2022/03/02/federator-ai-feature-demo-2/ - Categories: Intro/Demo Videos - Tags: Kubernetes, MachineLearning, MultiCloud, RedHat ProphetStor Federator. ai Feature Demo ProphetStor Federator. ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for the applications on Kubernetes. Using advanced machine learning algorithms to predict application workloads, Federator. ai scales the appropriate amount of resources at the right time for optimizing application performance and achieving cost savings. #Federator. ai, #Multicloud, #Machinelearning, #Kubernetes, #ProphetStor, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > We announce the onboarding of Evanston Technology Partners, which provides security, business intelligence and Cloud solutions, as a sales and technology partner. - Published: 2022-02-11 - Modified: 2024-01-15 - URL: https://prophetstor.com/2022/02/11/prophetstor-partners-with-evanstontec/ - Categories: Press Releases - Tags: AI, AIOps, ApplicationAware, Datadog, DevOps, DevSecOps, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, SUSE, Sysdig MILPITAS, CA, February 11, 2022 — We are delighted to announce the onboarding of Evanston Technology Partners as a sales and technology partner. Evanston Technology Partner has provided security, business intelligence, and Cloud solutions for their customers. ProphetStor’s Federator. ai solution can add to the portfolio to further help our joint customers automate and optimize their digital transformation journey. Under the leadership of Emmanuel Jackson, Evanston Technology Partners is also committed to uplifting the community. The team has been working with the top IT industry players to provide training and opportunities, which are life-changing for many youngsters in the community. ProphetStor is honored to partner and participate in the initiative by bringing in more collaboration for the company and offering training and certification to further Emmanuel’s vision. “I am happy that we can bring in ProphetStor’s solutions to enhance our value proposition to our customers further. We have been looking for great partnerships that offer innovative solutions and align our vision of transforming people, technology, and the community. ProphetStor is the right fit to empower us to help customers be more efficient, do more business, and cover more grounds with less complexity and cost. We are also delighted that we share the same belief in helping the community by offering the training and certifications that bring job opportunities,” said Emmanuel Jackson, CEO of Evanston Technology Partners. “I have this fantastic opportunity to know Emmanuel personally. He has been inspirational in his dedication to offering the best support for his customers... --- > Federator.ai 5.0 helps customers perform workload dynamics predictions and multi-layer impact analysis for a full-stack/deep understanding of applications. - Published: 2022-01-27 - Modified: 2024-01-15 - URL: https://prophetstor.com/2022/01/27/prophetstor-federator-ai-5-0/ - Categories: Press Releases - Tags: AI, AIOps, ApplicationAware, Datadog, DevOps, DevSecOps, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, SUSE, Sysdig MILPITAS, CA, January 27, 2022 — ProphetStor Data Services, Inc. today announced the general availability of Federator. ai 5. 0, a major release that helps customers automate and optimize their application performance and cost in a MultiCloud environment. Federator. ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, understands the application KPIs, takes the operation metadata, performs workload dynamics predictions and multi-layer impact analysis for a full-stack/deep understanding of applications. Furthermore, it provides intelligence for orchestrating Kubernetes container resources on virtual machines (VM) or bare metal. The added agility and efficiency allow users to operate applications without manually managing the underlying computing resources. Key features in Federator. ai 5. 0 include deep application KPI analysis, planning/simulation of application workloads and application resource tuning, and intelligent cost optimization for both clusters and applications. As a result, customers benefit from much reduced operational complexity as cost savings from continuous rightsizing resource allocations for clusters and applications. Federator. ai is also fully integrated with primary monitoring services such as Prometheus, Datadog, and Sysdig. It provides instant time-to-value for customers already using those monitoring services. Initial customer feedbacks show more than 35% in cost savings and more than 80% reduction in operational complexity with performance guarantees. Modern cloud-native applications consist of microservices that typically include front-end services and backend databases. An increase in external requests to an application has different impacts on individual microservices resource usages and key performance metrics. However, such impact is difficult to quantify and understand without deep analysis. Utilizing machine... --- > A quick description of how to achieve better performance and lower cost by auto-scaling Kafka consumers in Kubernetes environment, and a demo of how to configure an application on Federator.ai for Kafka consumer. - Published: 2021-10-15 - Modified: 2022-11-09 - URL: https://prophetstor.com/2021/10/15/how-to-configure-an-application-on-federator-ai-for-autoscaling-kafka-consumer/ - Categories: Setup Videos - Tags: AI, AIOps, Kubernetes, MachineLearning How to Configure An Application on Federator. ai for Autoscaling Kafka Consumer A quick description of how to achieve better performance and lower cost by auto-scaling Kafka consumers in Kubernetes environment, and a demo of how to configure an application on Federator. ai for Kafka consumer. #Federator. ai, #Kafka, #Kubernetes, #ProphetStor, #MachineLearning, #AI, #AIOps Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > A presentation in Kafka Summit on why intelligent autoscaling is better than Kubernetes native HPA - Published: 2021-09-15 - Modified: 2022-11-09 - URL: https://prophetstor.com/2021/09/15/intelligent-auto-scaling-of-kafka-consumers-with-workload-prediction/ - Categories: Seminar/ Webinar - Tags: Kubernetes, MachineLearning, MultiCloud Intelligent Auto-scaling of Kafka Consumers with Workload Prediction The following is the link to the recording and detailed presentation material illustrating why intelligent autoscaling is better than Kubernetes native HPA. Watch webinar recording and slides in Kafka Summit 2021 here: https://www. confluent. io/events/kafka-summit-americas-2021/intelligent-auto-scaling-of-kafka-consumers-with-workload-prediction/ #Federator. ai, #MultiCloud, #Machinelearning, #Kubernetes, #ProphetStor, #Kafka Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Federator.ai calculates the right number of consumer replicas based on predicted workload and target KPI metrics to determine the capabilities of consumer pods. - Published: 2021-09-13 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/09/13/intelligent-autoscaling-of-kafka-consumers-with-workload-prediction/ - Categories: blog - Tags: 5G, AI, AIOps, ApplicationAware, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift ProphetStor Federator.ai is an AI-based solution that helps enterprises manage and optimize resources for applications on Kubernetes. Introduction In a Kafka-based application, messages for specific topics are generated from some producers, and sent to the Kafka brokers. The brokers perform required replications and distribute messages to the consumers of the respective topics. After receiving messages from the brokers, a consumer will perform some tasks and let the brokers know the messages have been committed (or consumed). The zookeepers maintain the offset of the last message sent by a producer for a topic, and the offset of the last committed message notified by a consumer for a topic. When there is a burst of messages received by the brokers, the messages will be stored in the queues longer if a consumer cannot process the messages fast enough, affecting overall application performance. In order to handle the dynamic nature of message production rate, HPA or Horizontal Pod Autotscalling of the Kafka Consumers is used to scale the number of Kafka Consumers so that the production and consumption rates of a topic are matched while using a reasonable number of consumer replicas (minimize resource costs). At the same time, HPA also needs to maintain a low latency of processing messages, which is a KPI or Key Performance Index of Kafka Consumers. In particular, we are calibrating the number of replicas with the following trade-offs:Long latency if not enough ConsumersToo many consumers result in waste of resourcesThis article shows that the Native Kubernetes HPA algorithms (K8sHPA mechanism), based on either resource usages or KPI, result in modest savings and much larger... --- > Federator.ai 4.7 includes cost analysis and management, auto resource provisioning for applications, CICD integration, intelligent autoscaling, and free start. - Published: 2021-09-10 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/09/10/prophetstor-federator-ai-4-7/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, Sysdig MILPITAS, CA, September 10, 2021 — ProphetStor Data Services, Inc. today announced the general availability of Federator. ai 4. 7. Federator. ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, provides intelligence for orchestrating Kubernetes container resources on top of virtual machines (VM) or bare metal, allowing users to optimize infrastructure and application resources efficiently with automation. In addition, Federator. ai ML-based solution automatically identifies and recommends the actions needed for applications to run cost-effectively while maintaining performance goals. Significant features in Federator. ai 4. 7 include the following:Cost analysis and management – analyzes and reports cloud spending at namespace/project level, application level, and VM level based on workload predictions; recommends cost-reducing resource allocations for namespaces, applications, and VM nodesAuto resource provisioning for applications – provides closed-loop automation that adjusts application resource allocations with ML-based recommendation CI/CD Integration – continuous optimization of applications through the integration of Federator. ai with CI/CD pipeline and TerraformIntelligent autoscaling of upstream services of NGiNX Ingress – autoscales upstream containers based on the predicted workload of the Ingress controllerHistorical Data Analysis – accelerates the machine-learning process for infrastructure and application workload predictions and recommendations Free-Tier Availability– for optimizing up to 10 cluster nodes, namespaces, and containers “With the latest release of Federator. ai, customers can enjoy the benefits of machine learning-based intelligent workload predictions and recommendations for more efficient application deployment while reducing cloud costs. The auto-provisioning of application resources enables closed-loop automation that frees DevOps team from the manual reconfiguration of resource allocation,” said... --- > A quick tutorial on installing Federator.ai from Red Hat OpenShift Marketplace. - Published: 2021-08-16 - Modified: 2022-11-09 - URL: https://prophetstor.com/2021/08/16/installing-federator-ai-from-red-hat-marketplace/ - Categories: Setup Videos - Tags: AI, AIOps, MachineLearning, OpenShift, RedHat Installing Federator. ai from Red Hat Marketplace A quick tutorial on installing Federator. ai from Red Hat OpenShift Marketplace. #Federator. ai, #ProphetStor, #RatHat, #MachineLearning, #AI, #AIOps Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Federator.ai uses predictive analytics to capture the dynamic application workloads and optimizes resource usage and performance in the MultiCloud environments. - Published: 2021-07-27 - Modified: 2024-06-26 - URL: https://prophetstor.com/2021/07/27/federator-ai-optimizes-kubernetes-for-cost-and-performance/ - Categories: Intro/Demo Videos - Tags: HybridCloud, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat ProphetStor Federator. ai Optimizes Kubernetes for Cost and Performance ProphetStor's Federator. ai uses predictive analytics to analyze the dynamic workloads of Kubernetes applications and optimizes resource usage and performance in private, public, hybrid or multicloud environments. Red Hat Marketplace: https://marketplace. redhat. com/en-us/products/federatorai#Federator. ai, #Multicloud, #Machinelearning, #Kubernetes, #Hybridcloud, #ProphetStor, #RedHatMarketplace, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook ,and MediumConnect with ProphetStor on LinkedInProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Federator.ai, an AIOps solution for optimization of performance and cost savings, is available on Datadog Marketplace. Start for FREE! - Published: 2021-07-19 - Modified: 2024-10-21 - URL: https://prophetstor.com/2021/07/19/prophetstor-joins-datadog-marketplace/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud MILPITAS, CA, July 19, 2021 — ProphetStor Data Services, Inc. today announced the immediate availability of the company’s flagship AIOps solution Federator. ai through the Datadog Marketplace. Federator. ai is an AIOps platform that provides intelligence for orchestrating Kubernetes container resources on top of virtual machines (VM) or bare-metal servers, allowing users to operate applications without the need to manage the provisioning of the underlying computing resources manually. Datadog’s monitoring and security platform collects metrics, traces, logs, and more to provide observability for modern cloud environments. Using metrics from Datadog, Federator. ai provides machine learning-based predictions to make resource recommendations, and auto-scale containerized application workloads for Datadog customers. DevOps teams no longer need to constantly monitor the Kubernetes cluster utilization and manually adjust capacity. With resource recommendations from Federator. ai, DevOps teams can efficiently perform intelligent resource planning and significantly reduce over-provisioning costs. “We are thrilled to offer Federator. ai to Datadog customers through the Datadog Marketplace,” said Ming Sheu, EVP of Product, ProphetStor. “Rightsizing the container resources for cloud native applications is key to controlling your cloud spend while maintaining performance goals. By integrating metrics collected by Datadog, Federator. ai can help applications run in Kubernetes-based environments more efficiently and cost effectively. Datadog customers can also enjoy a single-pane-of-glass management with customized Datadog dashboards from Federator. ai. ” “As modern orchestrated environments become larger and more complex, it can be a challenge to understand and effectively scale your services,” said Michael Gerstenhaber, Senior Director of Product at Datadog. “We... --- > Federator.ai is an AI-based solution that helps enterprises manage and optimize resources for applications on Kubernetes. - Published: 2021-07-02 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/07/02/a-way-to-provision-cloud-workloads-with-federator-ai/ - Categories: blog - Tags: AI, ApplicationAware, GreenIT, Kubernetes, MachineLearning, OpenShift, SUSE ProphetStor Federator.ai is an AI-based solution that helps enterprises manage and optimize resources for applications on Kubernetes. The accelerated shift of running applications on-premises to running them in the cloud has taught many enterprises expensive lessons about managing pay-as-you-go pricing models. While some early missteps may be chalked up to inexperience, many large organizations continue to provision cloud resources ineffectively, and this is costing them well into the hundreds of thousands—sometimes millions—of dollars annually. As cloud adoption accelerates, the problem is getting worse. According to Gartner, public cloud workloads are forecast to rise 18% this year, while Flexera’s 2020 State of the Cloud Report estimates that 35% of cloud spend is wasted. Datadog, which monitors cloud app performance for thousands of enterprises, says that nearly half of the apps they monitor use 30% or fewer of the allocated resources. Manual, “gut check” approaches to allocating cloud resources are unsustainable. To avoid the performance impacts of under-provisioning, risk averse CloudOps teams commonly over-provision resources. And over-provision results in over-spending. There are two main reasons why highly skilled CloudOps teams struggle to get a tighter grip on provisioning. The first is that these teams lack visibility into the hosted services on which their apps run. The second is they lack the capabilities to predict what resources are needed. These teams also lack the tools to choose the most cost-optimized cluster configurations for their workloads. CloudOps teams need a new way to manage cloud resources that is automated and intelligent and looks at the full application stack—from the workload down to the container, the virtualized infrastructure layer, and individual hardware... --- > A quick tutorial on installing Federator.ai from SUSE/Rancher Marketplace. - Published: 2021-06-30 - Modified: 2022-11-09 - URL: https://prophetstor.com/2021/06/30/installing-federator-ai-from-suse-rancher-marketplace/ - Categories: Setup Videos - Tags: AI, AIOps, MachineLearning, SUSE Installing Federator. ai from SUSE/Rancher Marketplace A quick tutorial on installing Federator. ai from SUSE/Rancher Marketplace. #Federator. ai, #ProphetStor, #SUSE, #Rancher, #MachineLearning, #AI, #AIOps Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Learn how to integrate Federator.ai with Terraform to intelligently provision the right amount of resources to maximize the usage of their capacity. - Published: 2021-06-16 - Modified: 2022-10-28 - URL: https://prophetstor.com/2021/06/16/federator-ai-for-terraform-video/ - Categories: Setup Videos - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat ProphetStor Federator. ai CI/CD Integrationwith Terraform Learn how to integrate Federator. ai with Terraform to automatically and dynamically provision your containers with the right amount of resources that maintains performance objectives while reducing the cost. #OpenShift, #AI, #Multicloud, #Machinelearning, #Kubernetes, #ProphetStor, #Terraform Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > ProphetStor and Padok, a French Cloud solution company, become partners, that helps customers in EMEA achieve both application performance and cost objectives. - Published: 2021-06-11 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/06/11/prophetstor-partners-with-padok/ - Categories: Press Releases - Tags: AI, Kubernetes, MultiCloud, OpenShift, RedHat MILPITAS, CA, June 11, 2021 — ProphetStor Data Services, Inc. today announced its partnership with Padok, a French DevOps and Cloud solution company specializing in cloud expertise and the development of IT infrastructure projects, to help our joint customers to leverage the operation data for optimization in their cloud operations. The agreement illustrates ProphetStor’s commitment to the customers in this region to provide the best support to startups and big enterprises alike in Europe for their journey to the Cloud. Federator. ai, ProphetStor’s AIOps platform, uses advanced machine learning technology on operation data collected by monitoring service providers or solutions, such as Datadog, Sysdig, and Prometheus, to analyze and predict resource consumption and to recommend the Just-In-Time Fitted resources for performance and cost optimization. Padok can use the solution to help the customers that require reworks of their Cloud infrastructure based on the dynamics of the workloads. Customers can simultaneously achieve application performance and cost objectives by leveraging automation for continuous adaption and optimization offered by Federator. ai. “Large French groups which call on us have often tested the Cloud. However, they call on our help to migrate their critical infrastructure to the Cloud or launch large-scale projects, from POC to fully-operational,” said Padok CEO Clément David. “Our customers asked for visibility and security on the first phase of the journey to Cloud. However, the SLA and Cost of operation are becoming a major concern after they deploy the application to the Cloud. We are delighted to work with ProphetStor... --- > Integrated with Sysdig, Federator.ai offers workload predictions and right-sized resource recommendations for K8s clusters and applications on Sysdig. - Published: 2021-05-31 - Modified: 2024-06-26 - URL: https://prophetstor.com/2021/05/31/federator-ai-for-sysdig-video/ - Categories: Intro/Demo Videos - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat ProphetStor Federator. ai and Sysdig Integration By integrating operation metrics collected by Sysdig, Federator. ai, an ML-based platform, provides accurate predictions and just-in-time recommendations for resource allocation and autoscaling, and eliminates complexity and uncertainty that impact IT operations. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- - Published: 2021-05-24 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/05/24/infographic-federator-ai-multilayer-correlation/ - Categories: Infographics - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat Value Proposition of Federator. ai Why Federator. ai Application behaviors are dynamic and optimization are hard, so ProphetStor Federator. ai is here to help. Federator. ai can do prediction of the application behavior and constructing the multi-layer correlation and causality analysis for full stack behavior prediction and optimization, which can save of 1000s times of resources for building predictive models for layers. For more information, please see the following infographic. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Integrated with Datadog, Federator.ai offers workload predictions and right-sized resource recommendations for K8s clusters and applications on Datadog. - Published: 2021-05-18 - Modified: 2024-06-26 - URL: https://prophetstor.com/2021/05/18/federator-ai-for-datadog-video/ - Categories: Intro/Demo Videos - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat ProphetStor Federator. ai and Datadog Integration With integration to Datadog, ProphetStor’s Federator. ai provides workload predictions and right-sized resource recommendations for Kubernetes clusters and containerized applications, all in a single-pane-of-glass management console using Datadog dashboards. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat, Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- - Published: 2021-04-21 - Modified: 2022-03-11 - URL: https://prophetstor.com/2022/03/02/federator-ai-feature-demo - Categories: Setup Videos - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat ProphetStor Federator. ai Feature Demo With ProphetStor Federator. ai, you can easily manage, optimize, and auto-scale resources for any applications on Kubernetes. Check out our feature demo to know more about Federator. ai: #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat, Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > ProphetStor Federator.ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for any applications on Kubernetes. Using advanced machine learning algorithms to predict application workloads, Federator.ai scales the appropriate amount of resources at the right time for optimized application performance. - Published: 2021-04-20 - Modified: 2022-11-09 - URL: https://prophetstor.com/2021/04/20/federator-ai-installation-and-configuration/ - Categories: Setup Videos - Tags: AI, AIOps, Kubernetes, MachineLearning ProphetStor Federator. ai Installation and Configuration ProphetStor Federator. ai is an AI-based solution that helps enterprises manage, optimize, and auto-scale resources for any applications on Kubernetes. Using advanced machine learning algorithms to predict application workloads, Federator. ai scales the appropriate amount of resources at the right time for optimized application performance. #Federator. ai, #Kubernetes, #ProphetStor, #MachineLearning, #AI, #AIOps Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > Federator.ai, an AIOps platform, collects operation metrics from Sysdig, a secure DevOps company, to achieve data-driven intelligence in a single-pane console. - Published: 2021-03-15 - Modified: 2024-01-16 - URL: https://prophetstor.com/2021/03/15/prophetstor-brings-intelligent-kubernetes-orchestration-to-sysdig-customers/ - Categories: Press Releases - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat MILPITAS, CA, March 15, 2021 — ProphetStor Data Services, Inc. today announced the general availability of Federator. ai 4. 4. Federator. ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, provides intelligence for orchestrating Kubernetes container resources on top of virtual machines (VM) or bare metal, allowing users to operate applications without the need to manage the underlying computing resources manually. Key features in the latest Federator. ai release include Spot instance recommendations for MultiCloud cost analysis and the support of metrics collected by Sysdig, a secure DevOps company that helps organizations secure containers, Kubernetes, and cloud services. Utilizing metrics from Sysdig, Federator. ai provides AI/Machine Learning-based predictions for containerized application workloads and cluster node resource usages as the basis for resource recommendations to joint Sysdig and ProphetStor customers. DevOps no longer needs to monitor the Kubernetes cluster utilization constantly and manually adjust capacity. With resource recommendations from Federator. ai, DevOps can efficiently perform intelligent resource planning and significantly reduce over-provisioning costs. The application-aware workload prediction also enables Federator. ai to auto-scale application pods via extension API server, providing fitted resources for optimal performance. “With the latest release of Federator. ai, Sysdig customers can enjoy the benefits of AI-based intelligent workload predictions using application and cluster node metrics from Sysdig. Joint customers can easily view the prediction results and recommendations from the integrated Sysdig dashboards, all from the same single pane of glass. ” said Tad Lebeck, EVP of Business Development, ProphetStor. “Also, Federator. ai analyzes evictable application workloads and... --- > In this webinar, we show how Datadog and ProphetStor help teams to solve the challenges in deploying containerized applications on OpenShift by bringing end-to-end visibility and resource optimization recommendations to meet application performance and cost requirements. - Published: 2021-02-26 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/02/26/joint-webinar-with-datadog/ - Categories: Seminar/ Webinar - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat The following is the link to the recording and detailed presentation material illustrating how ProphetStor and Datadog help teams to solve the challenges in deploying containerized applications on OpenShift. Watch webinar recording here: https://www. bigmarker. com/mediaops/Learn-How-to-Use-Datadog-and-Prophetstor-to-Monitor-and-Optimize-Openshift-Container-Resources? bmid=d605a1cc049b Webinar slides can be found here: https://www. slideshare. net/JadeCampbell13/understanding-and-rightsizing-container-resources-with-datadog-and-prophetstor OpenShift enables organizations to accelerate delivery cycles and rapidly scale their operations to meet the demands of today's fast-paced market. For example, individual application teams can deploy multiple versions every day on common infrastructure, and scale their applications to meet the demand of their users. However, Datadog's recent containers study found that the majority of OpenShift and Kubernetes workloads are underutilizing CPU and memory resources. In this webinar, we show how Datadog and ProphetStor help teams to solve the challenges in deploying containerized applications on OpenShift by bringing end-to-end visibility and resource optimization recommendations to meet application performance and cost requirements. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow... --- > Prophetstor Federator.ai brings machine learning to make Kubernetes automated Application-Aware and Workload-Sensible, which can save your operation cost and improve applications performance at the same time. - Published: 2021-02-19 - Modified: 2024-01-15 - URL: https://prophetstor.com/2021/02/19/infographic-federator-ai/ - Categories: Infographics - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat Value Proposition of Federator. ai Why KubernetesKubernetes makes a breakthrough for DevOps because it allows teams to keep pace with the requirements of modern software development. Its agile, fault-tolerant, auto-scaling make it trending in industries. However, Kubernetes is also complicated to configure and heuristic in operation. Why Federator. aiTo deal with this predicament, Prophetstor's Federator. ai brings machine learning to make Kubernetes automated Application-Aware and Workload-Sensible, which can save your operation cost and improve applications performance at the same time. For more information, please see the following infographic. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > The latest Federator.ai 4.4, including Spot instance recommendations for Multicloud cost analysis, is available to Sysdig customers - Published: 2021-02-09 - Modified: 2024-01-16 - URL: https://prophetstor.com/2021/02/09/prophetstor-federator-4-4-release/ - Categories: Press Releases - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat MILPITAS, CA, February 9, 2021 — ProphetStor Data Services, Inc. today announced the general availability of Federator. ai 4. 4. Federator. ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, provides intelligence for orchestrating Kubernetes container resources on top of virtual machines (VM) or bare metal, allowing users to operate applications without the need to manage the underlying computing resources manually. Key features in release 4. 4 include Spot instance recommendations for Multicloud cost analysis and the support of metrics collected by the Sysdig Monitoring platform. Utilizing metrics from the Sysdig cloud monitoring service, Federator. ai provides AI/Machine Learning based predictions for containerized application workloads and cluster node resource usages as the basis for resource recommendations to Sysdig customers. DevOp no longer needs to monitor the Kubernetes cluster utilization constantly. With resource recommendations from Federator. ai, DevOp can efficiently perform intelligent resource planning and significantly reduce over-provisioning costs. The application-aware workload prediction also enables Federator. ai to auto-scale application pods vis extension API server, providing just enough resources for optimal performance. “With the release of Federator. ai 4. 4, Sysdig customers can enjoy the benefits of AI-based intelligent workload predictions using application and cluster node metrics from Sysdig. Customers can easily view the prediction results and recommendations from the integrated Sysdig Dashboards, all from the same single pane of glass,” said Ming Sheu, EVP of Products, ProphetStor. “Also, Federator. ai 4. 4 analyzes evictable application workloads and provides the most cost-effective Spot instance recommendations while maintaining required resources for these... --- > Fedemeter, the patent-pending cost analysis module of Federator.ai, takes the input of current cluster configuration and workload prediction to produce a recommendation of the most cost-optimized cluster configuration for users. - Published: 2020-12-29 - Modified: 2024-01-15 - URL: https://prophetstor.com/2020/12/29/infographic-fedemeter/ - Categories: Infographics - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat Value Proposition of Fedemeter Orchestrate, optimize and manage your costs in public cloud, hybrid cloud, or multi-cloud Fedemeter, the patent-pending cost analysis module of Federator. ai, takes the input of current cluster configuration and workload prediction to produce a recommendation of the most cost-optimized cluster configuration for users. The recommendation output is a time series of Just-in-Time Fitted instance size to support application workloads without resource wastes. The most cost-effective instance types with the best purchasing options are recommended. For more information, please see the following infographic. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- - Published: 2020-12-21 - Modified: 2024-01-15 - URL: https://prophetstor.com/2020/12/21/openshift-tv-program-dec-16-2020/ - Categories: Seminar/ Webinar - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat Mike Waite, Senior Principal Product Marketing at Red Hat, interviewed ProphetStor CEO Eric Chen and EVP of Products Ming Sheu on OpenShift TV on December 16, 2020, to talk about ProphetStor’s vision and mission. ProphetStor has been working on AI-enabled proactive management to address the complexity in Hybrid MultiCloud environments. Ming also showed a demo about the Federator. ai integration with Datadog Monitoring Services. The following is a link to the recording and detailed presentation material illustrating how ProphetStor provides the solutions and how it brings customers’ values to optimize the cost and performance in Hybrid MultiCloud operations. https://www. youtube. com/watch? v=qGhYhaYdztcPlease see the following for more about the interview. Who are WeWe are a group of industry veterans with expertise in IT management, Infrastructure and Cloud Operations, Data Sciences, and AI technologies. We share the vision that the purpose of the IT Infrastructures and Cloud Services is to ensure that the purposes of the applications can be served and that they need to be proactive and upfront to avoid afterthoughts. The complexity of the operation can be minimized, cost saved, and performance optimized if we can understand the workload behaviors and match the requirements with the right amount of resources at the right time. Why We Want to Do ThisManaging the existing IT infra and Cloud operations are all very passive tasks, requiring a lot of human ingenuity. The situation worsens when we bring in the containerized applications, the dev/ops operation, and the new MultiCloud paradigms. Besides, workloads are... --- > Tad Lebeck has joined its executive team, which brings to ProphetStor more than 30 years of professional experience in enterprise software and cloud solution from Legato, Symantec, Veritas, and Huawei-Symantec, to name a few. - Published: 2020-12-07 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/12/07/prophetstor-adds-to-its-executive-business-development-team/ - Categories: Press Releases - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat MILPITAS, CA, December 7, 2020 — ProphetStor Data Services, Inc. has been a pioneer in bringing AI-enabled solution to address the complexity and efficacy of the MultiCloud, Edge Computing, and 5G platforms. Today, ProphetStor announces that Tad Lebeck has joined its executive team as the Executive Vice President of Business Development. Mr. Lebeck will lead ProphetStor’s effort to foster strong partnerships with industry leaders and bring our core values to the customers. Tad brings to ProphetStor more than 30 years of professional experience in enterprise software and cloud solution from Legato, Symantec, Veritas, and Huawei-Symantec, to name a few. Since its inception, he has been serving as a technical advisory board member of ProphetStor, inspiring ProphetStor with company strategy, product definitions, and market positioning. He also co-founded several companies to address the complexity of Kubernetes operations. “I am excited to join ProphetStor and to be part of this impressive team’s journey delivering a game-changing solution. Federator. ai uniquely addresses Kubernetes operations’ complexities with application awareness, multi-layer correlation and prediction, reinforcement learning, and delivering unparalleled performance and cost optimization. The company is poised for exponential growth,” said Tad Lebeck, EVP of Business Development of ProphetStor. “Tad has played many important roles in the industry and has successfully pioneered products that serve enterprises and Cloud Services. We are thrilled to have him join the executive team of ProphetStor and lead the business development team to address our customers’ and partners’ needs in the enterprise, cloud, and telecom industries. I am confident that... --- - Published: 2020-11-25 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/11/25/prophetstor-expands-taipei-operation/ - Categories: Press Releases - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat MILPITAS, CA, November 25, 2020 — ProphetStor is delighted to announce the opening of its new and expanded Taipei office to house additional sales, support, and engineering headcounts and resource to meet the increasing demands in this region. With the surging of the market for the 5G, Edge Computing, and Hybrid MultiCloud even during the pandemic, the expansion assures the partners and customers that ProphetStor can provide them with the resources needed. “We have witnessed the firm acceptance of the Kubernetes platforms as the operating systems in 5G and Hybrid MultiCloud. The APAC market is experiencing a hyper-growth in Cloud and 5G infrastructure building, accepting the open solutions. The Taipei office’s expansion shows our commitment to provide the best support for our OEM partners and the increasing customer base in this region. We are also happy to know that ProphetStor’s innovative Federator. ai management platform offers the differentiation in our partners’ total solutions in optimizing the performance and cost when their products are in operation in 5G and Hybrid MultiCloud,” said ProphetStor CEO Eric Chen. #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat, Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and... --- - Published: 2020-11-11 - Modified: 2022-11-09 - URL: https://prophetstor.com/2020/11/11/joint-webinar-with-red-hat/ - Categories: Seminar/ Webinar - Tags: AI, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, ResourceManagement A joint webinar with Red Hat on how Federator. ai optimizes resource management on OpenShift. Watch webinar recording here: https://www. youtube. com/watch? v=93bPFk5RCoc#machinelearning, #AI, #openshift, #HybridCloud, #resourcemanagement, #Kubernetes, #federatorai, #ProphetStor, #RedHat, #Multicloud, #orchestration Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > The Interview with Manager of 'XaaS' Cloud Department at Orange. - Published: 2020-10-30 - Modified: 2022-11-09 - URL: https://prophetstor.com/2020/10/30/see-how-prophetstor-helps-orange-france/ - Categories: Intro/Demo Videos - Tags: AI, GreenIT, Kubernetes, MachineLearning, MultiCloud See How ProphetStor Helps Orange France The Interview with Frédéric Klein, Manager of 'XaaS' Cloud Department, at Orange. #Federator. ai, #MultiCloud, #Machinelearning, #Kubernetes, #ProphetStor, #OrangeFrance, #AI, #GreenIT Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services for the operation to help enterprises and cloud service providers build agile, automated, cost-effective, intelligent, and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based networked storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com. Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- - Published: 2020-09-15 - Modified: 2022-11-09 - URL: https://prophetstor.com/2020/09/15/video-red-hat-summit-2019-prophetstor-federator-ai-demo/ - Categories: Seminar/ Webinar - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat Red Hat Summit 2019 - ProphetStor Federator. ai Demo #OpenShift, #AI, #Multicloud, #HybridCloud, #Kubernetes, #ProphetStor, #RedHat, Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform, provides AI-enabled federated data services to help both enterprises and cloud service providers to build agile, automated, cost-effective, intelligent and orchestrated IT and Cloud infrastructures. ProphetStor was founded in 2012 by seasoned IT experts with extensive experience in cloud computing platforms, software-based network storage, data services, and AI technology. Headquartered in Milpitas, California, ProphetStor has branch offices in Asia-Pacific and European regions to serve international customers. For more information, visit https://prophetstor. com Additional Resources Follow ProphetStor on Twitter, Facebook and Medium Connect with ProphetStor on LinkedIn ProphetStor Federator. ai is a registered trademark of ProphetStor Data Services, Inc. in the US and other countries. All other company and product names contained herein may be trademarks of their respective holders. --- > ProphetStor's flagship solution Federator.ai, which uses advanced machine learning technologies, is now available through Red Hat Marketplace. - Published: 2020-09-08 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/09/08/red-hat-marketplace/ - Categories: Press Releases - Tags: AI, HybridCloud, Kubernetes, MultiCloud, OpenShift, RedHat Red Hat Marketplace provides a one-stop-shop to purchase enterprise applications and deploy across any cloud or on-premise MILPITAS, CA, September 8, 2020 — ProphetStor Data Services, Inc. today announced that its flagship solution Federator. ai is now available through Red Hat Marketplace. Red Hat Marketplace is an open cloud marketplace for enterprise customers to discover, try, purchase, deploy, and manage certified container-based software across environments—public and private, cloud and on-premises. Through the marketplace, customers can take advantage of responsive support, streamlined billing and contracting, simplified governance, and single-dashboard visibility across clouds. Federator. ai uses advanced machine learning technologies to help enterprises optimize cloud resources and application performance. With Federator. ai, enterprises can now perform effective capacity planning and resource optimization on their clouds, and auto-scale the resources for each application with the best performance. The use of Federator. ai ensures that there is no excessive over-provisioning nor under-provisioning of cloud resources for each application. Built in collaboration with Red Hat and IBM, Red Hat Marketplace delivers a hybrid multicloud trifecta for organizations moving into the next era of computing: a robust ecosystem of partners, an industry-leading Kubernetes container platform, and award-winning commercial support—all on a highly scalable backend powered by IBM. A private, personalized marketplace is also available through Red Hat Marketplace Select, enabling clients to provide their teams with easier access to curated software their organizations have pre-approved. “We are excited to join the new Red Hat Marketplace and collaborate with Red Hat and IBM to deliver Federator. ai,... --- - Published: 2020-08-31 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/08/31/prophetstor-is-granted-a-patent-on-modeling-application-workloads-to-automate-the-management-and-to-predict-the-anomalies-of-storage-resources-in-multicloud-environments/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent MILPITAS, CA, August 31, 2020 — ProphetStor Data Services, Inc. was assigned the patent “METHOD AND SYSTEM FOR STORAGE TRAFFIC MODELING“ (Patent number US 9,906,424) by the United States Patent and Trademark Office. The patent is a foundation for software-defined data centers where the requirement of flexible adjustment of resources in meeting application demands can only be fulfilled when the workload can be modeled and predicted. ProphetStor’s Federator. ai employs application-awareness and workload prediction as the basis for resource allocation and adaptation to meet the requested SLA, to optimize performance, and to drastically reduce the cost of over-provisioning. With this patented technology, it is now possible to automate the management and to predict the anomalies of the storage resources using Machine Learning technologies. The understanding of future behaviors of storage and other resources can further benefit the sustainability of a cloud center as it helps optimize placement of workloads and resolve issues before they turn into problems. Furthermore, it can trigger auto-migration when the resource is failing or when the resource could not support the required performance. Therefore, supporting continuous operation of the applications becomes possible. “Application workloads are dynamic. However, in the past, the common practices in resource allocation for applications are static and over-provisioned, creating wastes and uncertainties. Without proper modeling, planning and optimization are not achievable. Together with the previously patented technologies, ProphetStor’s newly granted patent makes it possible to deliver dynamic resource allocation for applications. The modeling of the application workload can turn the guesswork of... --- - Published: 2020-08-24 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/08/24/prophetstor-brings-machine-learning-based-intelligent-kubernetes-orchestration-to-datadog-customers/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat ProphetStor Data Services, Inc. today announced the general availability of Federator.ai 4.3 for Datadog. Federator.ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, provides intelligence for orchestrating Kubernetes container resources on top of virtual machines (VM) or bare metal, allowing users to operate applications without the need to manually manage the underlying computing resources. MILPITAS, CA, August 24, 2020 — ProphetStor Data Services, Inc. today announced the general availability of Federator. ai 4. 3 for Datadog. Federator. ai, ProphetStor’s Artificial Intelligence for IT Operations (AIOps) platform, provides intelligence for orchestrating Kubernetes container resources on top of virtual machines (VM) or bare metal, allowing users to operate applications without the need to manually manage the underlying computing resources. Utilizing metrics from Datadog, Federator. ai provides AI/Machine Learning based predictions for containerized application workloads and cluster node resource usages as the basis for resource recommendations. This frees DevOp from constantly monitoring the Kubernetes cluster utilization. With resource recommendations from Federator. ai, DevOp can easily perform intelligent resource planning and greatly reduce the cost of over-provisioning. The application-aware workload prediction also enables Federator. ai to auto-scale application pods via Datadog’s WPA, providing just enough resources for optimal performance. Additionally, Federator. ai provides cost analysis from a multi-cloud perspective utilizing the intelligent workload predictions and recommendations. “With the release of Federator. ai 4. 3 for Datadog, all Datadog customers can enjoy the benefits of AI-based intelligent workload predictions using application and cluster node metrics from Datadog,” said Ming Sheu, EVP of Products, ProphetStor. “In addition to the easy-to-use Federator. ai user interface, customers can view the prediction results and recommendations from the integrated Datadog Dashboards, all from the same single pane of glass. Furthermore, taking advantage of the powerful Datadog monitoring platform, our integrated monitors alert users the potential resource shortage according to the Federator. ai’s resource usage... --- - Published: 2020-08-17 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/08/17/prophetstor-is-granted-a-foundation-patent-on-adapting-infrastructure-resource-deployments-according-to-the-lifecycle-of-application-workloads/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR DEPLOYING STORAGE SYSTEM RESOURCES WITH LEARNING OF WORKLOADS APPLIED THERETO“ (Patent number US 10,013,286) by the United States Patent and Trademark Office. MILPITAS, CA, August 17, 2020 — ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR DEPLOYING STORAGE SYSTEM RESOURCES WITH LEARNING OF WORKLOADS APPLIED THERETO“ (Patent number US 10,013,286) by the United States Patent and Trademark Office. The patented technology is a pillar of the foundation in ProphetStor’s Federator. ai platform that uses application-awareness and workload prediction as the basis for resource allocation and adaptation to meet the requested SLA, to optimize performance, and to reduce the cost of over-provisioning. In contrast to the conventional wisdom of virtualization based on fixed capacity assignment throughout the lifetime of an application, ProphetStor believes that the infrastructure resources should be adaptive by serving the applications according to their KPI, priority, and dynamic requirements in performance and capacity. Federator. ai builds models with Deep Learning and mathematics/statistical methods to create accurate predictions for applications. Federator. ai brings intelligibility to planning, performance enhancement, and just-in-time fitted resource allocation. ProphetStor has been devoting its innovation in bringing Machine Learning to IT operations since it was founded in 2012. The patented technology is the foundation of our solutions to Kubernetes ecosystems, which are now commonly used for Hybrid MultiCloud, 5G, and Edge Computing that require automation and operational efficiency. “We believe the resource allocation in Hybrid MultiClouds and 5G edge to core should be adaptive according to application types, SLA requirements, and workloads in its lifecycle. However, optimization of the scheduling and scaling is a very complicated task. ProphetStor’s newly granted patent tackles this issue by... --- - Published: 2020-08-10 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/08/10/prophetstors-patent-on-meeting-applications-future-demands-is-the-foundation-for-viable-aiops-and-machine-learning-for-system-operation/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR OPTIMIZING STORAGE CONFIGURATION FOR FUTURE DEMAND AND SYSTEM THEREOF“ (Patent number US 10,067,704) by the United States Patent and Trademark Office. MILPITAS, CA, August 10, 2020 — ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR OPTIMIZING STORAGE CONFIGURATION FOR FUTURE DEMAND AND SYSTEM THEREOF“ (Patent number US 10,067,704) by the United States Patent and Trademark Office. The patented technology has been incorporated into ProphetStor’s Federator. ai platform that uses prediction of the application workloads as the basis for resource allocation and adaptation to meet the requested SLA. Deep Learning and math models are used to create accurate predictions of FUTURE workloads so that the planning, performance enhancement, and resource allocation in Cloud and Telecom services can be simplified with reduced computational cost. ProphetStor has been devoting its innovation in applying Machine Learning in IT operations since it was founded in 2012. The patented technology is a part of its efforts to manage the complexity of automating and optimizing the operations in Kubernetes ecosystems, Cloud, and Zero-Touch operation in 5G. “We believe the resource allocation in Clouds and in the 5G edge to core network should be adaptive according to the application workloads. ProphetStor’s newly granted patent illustrates that prediction could help simplify the operation by bringing in intelligence about the applications and the infrastructure. The prediction of application workload, coupled with the Multi-Layer Correlation and Impact Analysis, can effectively reduce the computation resources needed for planning and operation,” said Eric Chen, CEO of ProphetStor. “Working from the top of the application stack, and analyzing the correlation from the top layer down, we can achieve the reduction in the computational cost... --- > At the heart of the IT technology, it is the applications that need to be ultimately supported. ProphetStor brings the essence of workload awareness to its design philosophy for optimization in resource allocation and workload placement. - Published: 2020-08-03 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/08/03/prophetstors-patent-on-ai-powered-workload-aware-framework-becomes-the-foundation-of-aiops-for-optimization-in-multicloud-and-5g-2/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor Data Services, Inc. was assigned the patent “WORKLOAD-AWARE I/O SCHEDULER IN SOFTWARE-DEFINED HYBRID STORAGE SYSTEM“ (Patent number US 9,575,664) by the United States Patent and Trademark Office. MILPITAS, CA, August 03, 2020 — ProphetStor Data Services, Inc. was assigned the patent “WORKLOAD-AWARE I/O SCHEDULER IN SOFTWARE-DEFINED HYBRID STORAGE SYSTEM“ (Patent number US 9,575,664) by the United States Patent and Trademark Office. The patented technology has been incorporated into ProphetStor’s Federator. ai platform that leverages application awareness for scheduling resources in a Just-In-Time Fitted manner for application workloads. The technology results in much improved performance and utilization for general IT and Kubernetes platforms that have become the “Operating Systems” for MultiCloud and 5G Network operations. As Dr. Jeff Dean of Google Brain stated in his 2019 article that “The potential exists to use machine-learned heuristics to replace hand-coded heuristics, with the ability for these ML heuristics to take into account much more contextual information than is possible in hand-written heuristics, allowing them to adapt more readily to the actual usage patterns of a system. ” The patented technology of ProphetStor lays the foundation of bringing the digital intelligence into Cloud and 5G operations to address both the complexity and efficiency issues that are very difficult to be automated. ProphetStor has been focusing its innovation in applying Machine Learning in IT operations since it was founded in 2012. This patent grant is a recognition of our vision. “ProphetStor started its journey of Application-Aware AIOps first by its invention in storage performance virtualization to improve the conventional storage capacity virtualization,” said Dr. Ming Sheu, ProphetStor’s EVP of Products. “At the heart of the IT technology, it is the applications that... --- - Published: 2020-07-27 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/07/27/prophetstor-adds-to-its-executive-team-with-industry-veteran/ - Categories: Press Releases - Tags: AIOps, Datadog, Kubernetes, OpenShift, RedHat ProphetStor Data Services, Inc. has been striving to bring its AI-enabled solution to address the complexity and efficacy of the MultiCloud, Edge Computing, and 5G platforms. Today, ProphetStor announced that Dr. Ming Sheu had joined its executive team as the Executive Vice President of Products, in charge of industry alliances, product developments and deliveries. MILPITAS, CA, July 27, 2020 — ProphetStor Data Services, Inc. has been striving to bring its AI-enabled solution to address the complexity and efficacy of the MultiCloud, Edge Computing, and 5G platforms. Today, ProphetStor announced that Dr. Ming Sheu had joined its executive team as the Executive Vice President of Products, in charge of industry alliances, product developments and deliveries. He will be leading our products to address our next level markets and the company as a Data Services company. Dr. Sheu brings to ProphetStor close to 30 years of professional experience from IBM, RapidStream, Accton, Ruckus Networks, Brocade, Arris, and CommScope. He is known in the industry for bringing carrier-grade products to the market and has been managing teams spanning US, China, India, Israel, and Taiwan. Before joining ProphetStor he was the VP of Cloud Engineering at Ruckus Networks, responsible for the development of a next-generation cloud-native, microservice-based network management-as-a-service product. “I am happy to join ProphetStor and to be part of a great team’s journey to deliver the game-changing solution, Federator. ai, for addressing the complexity and efficiency of operating Kubernetes platforms that are becoming the cores of MultiCloud, Edge Computing, and 5G. ProphetStor already has an impressive patent portfolio that defines them as a pioneer in the AIOps for container management. The team is ready for the next phase of exponential growth,” says Dr. Ming Sheu, EVP of Products of ProphetStor. “Dr. Sheu has played many important roles in the industry and has successfully delivered cornerstone products... --- - Published: 2020-07-20 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/07/20/prophetstors-patent-on-ai-based-methods-in-predicting-the-life-span-of-storage-systems-facilitates-proactive-management-to-support-slas-and-reduce-operation-costs-in-data-and-cloud-centers/ - Categories: Press Releases - Tags: AIOps, Datadog, DiskFailure, Kubernetes, OpenShift, RedHat, USAPatent ProphetStor Data Services, Inc. was assigned the patent “METHOD AND SYSTEM FOR DIAGNOSING REMAINING LIFETIME OF STORAGES IN DATA CENTER“ (Patent number US 10,606,722) by the United States Patent and Trademark Office. MILPITAS, CA, July 20, 2020 — ProphetStor Data Services, Inc. was assigned the patent “METHOD AND SYSTEM FOR DIAGNOSING REMAINING LIFETIME OF STORAGES IN DATA CENTER“ (Patent number US 10,606,722) by the United States Patent and Trademark Office. The patented technology has been incorporated in ProphetStor’s Federator. ai platform that leverages the multi-layer operation data collected by monitoring software or services. These operation data include metrics from application logs, virtualization platforms, cloud service providers, and infrastructures. The technology can also be applied to the life span predictions of other components in an IT environment. With this innovation, Federator. ai can continuously work on collected data, including the health of the disks and storage systems and application workloads, to produce predictions for the life spans of the storage systems. It becomes the foundation of AIOps (AI in IT Operations) in a data center or a cloud center, effectively changing the conventional reactive issue resolution approach to pro-active maintenance efforts. The solution is also essential in the 5G networks to enable the “Zero-Touch” operations. “Delivering needed SLA and minimizing the complexity and cost of operations in the Data and Cloud Centers are essential in the movements to the Cloud. Predictivity brings transparency, and that, in turn, brings operation efficiency. ProphetStor is delighted to be recognized for its innovative technology through this patent grant. We have incorporated the technology in all of our product lines and have brought tremendous values to customers. The customers, ranging from storage vendors, professional service teams, data and cloud... --- > France Télécom S.A., the 4th largest mobile network operator in Europe, uses Federator.ai for auto-scaling, optimizing resources and application performance on its MultiCloud infrastructure. - Published: 2020-07-09 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/07/09/orange-france-uses-federator-ai-for-auto-scaling-optimizing-resources-and-application-performance-on-its-multi-cloud-infrastructure/ - Categories: Press Releases - Tags: AI, GreenIT, MultiCloud ProphetStor Data Services, Inc. today announced that Orange S.A. in France (abbrev. Orange) has deployed Federator.ai for managing resources, optimizing costs and application performance on its Kubernetes-based multicloud infrastructure. MILPITAS, CA, July 09, 2020 — ProphetStor Data Services, Inc. today announced that Orange S. A. in France (abbrev. Orange) has deployed Federator. ai for managing resources, optimizing costs and application performance on its Kubernetes-based multicloud infrastructure. Orange is a major telecom operator (largest in France, 4th largest in Europe) and operates mobile, landline, Internet and IPTV services. Orange continues to utilize state-of-the-art technologies in ensuring the most advanced and reliable service delivery to its more than 260 million customers worldwide. Similar to other leading technology enterprises around the world, Orange is currently developing many new applications on a cloud-native architecture and will deploy these new applications in a multicloud environment. As these new applications have highly dynamic workloads and specific service-level requirements, Orange has been searching for innovative solutions to help manage the cloud resources for supporting each of these applications at scale, and at the same time optimizing the cost and application performance. Federator. ai, the leading solution in optimizing resources and application performance on Kubernetes, uses advanced artificial intelligence technologies to address the above needs of Orange in managing their cloud operations. With Federator. ai, Orange can now auto-scale the resources for each of their dynamic applications on Kubernetes clusters with the best performance, as well as performing effective capacity planning and resource optimization for all applications at scale. The use of Federator. ai ensures that there is no excessive over-provisioning nor under-provisioning of cloud resources for each application at Orange. “Federator. ai can be easily installed... --- > The Federator.ai and Datadog integration allows customers to get AI-enabled recommendations for HPA based on observability into applications’ resource utilization. - Published: 2020-06-24 - Modified: 2024-01-16 - URL: https://prophetstor.com/2020/06/24/prophetstor-joins-datadog-partner-network-as-a-technology-partner-and-offers-integrated-intelligent-orchestration-solutions-to-joint-customers/ - Categories: Press Releases ProphetStor Data Services, Inc. today announced that the company has joined Datadog (NASDAQ: DDOG) Partner Network as a Technology Partner, and the integration of Federator.ai with Datadog’s monitoring services. MILPITAS, CA, June 24, 2020 — ProphetStor Data Services, Inc. today announced that the company has joined Datadog (NASDAQ: DDOG) Partner Network as a Technology Partner, and the integration of Federator. ai with Datadog’s monitoring services. The Federator. ai and Datadog integration will allow customers to get full observability into their applications’ resource utilization along with the AI-enabled recommendations from Federator. ai for real time Horizontal Pod Autoscaling (HPAs). ProphetStor’s Federator. ai leverages multi-layer operational data, including the metrics from applications, Kubernetes, cloud service providers, and underlying infrastructure that Datadog collects. The data is adapted, and then processed by the ProphetStor’s patented and Deep Learning based Data Correlation and Impact Prediction Engine (DCIE) to create intelligent operation plans. When used for Kubernetes platforms, the Federator. ai creates Application-aware, Just-in-Time, and Fitted resource allocation operational plans for Kubernetes Pod Autoscaling. Additionally, Federator. ai enables workload prediction optimization of application and cloud service usage, making it easier and more efficient to deploy containerized applications. Datadog's monitoring and security platform helps users collect and analyze infrastructure metrics, distributed traces, and logs, so teams can scale their environments with confidence. Datadog also makes it easy to monitor applications running on Kubernetes with solutions such as Datadog Agent, and Cluster Agent. Furthermore, Datadog published a free open-source software called Watermark Pod Autoscaler (WPA) to extend the features of the HPA, and give users more control over autoscaling their clusters. With the integration of the Federator. ai and Datadog’s autoscaling solution, ProphetStor brings proactive resource management... --- > Using metrics from Datadog, Federator.ai provides AI-based predictions to make recommendations and auto-scale containerized application workloads on Kubernetes. - Published: 2020-06-17 - Modified: 2024-01-15 - URL: https://prophetstor.com/2020/06/17/federator-ai-ai-solution-for-auto-scaling-on-kubernetes-with-datadog/ - Categories: blog - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent With Datadog, our enterprise customers are now able to monitor their application workloads and get visibility into Kubernetes clusters of any scale. The new integration between Federator. ai and Datadog has made it easier to deploy our service, collect and monitor any metrics (e. g. CPU and memory utilization, application latency etc) for applications running on Kubernetes. Similar to our Federator. ai Operator, Datadog has received RedHat OpenShift Operator Certification, meaning that it has been tested to work with OpenShift and screened for security risks. Many of our enterprise customers today are running hundreds or even thousands of containerized applications at the same time while sharing a common pool of cloud resources on-premises or in the public clouds. In addition, these application workloads are quite dynamic in nature and sometimes could increase drastically (10-100x) during specific periods of time, and accordingly, the resources should be increased during such periods and then be decreased afterwards. However, enterprises typically do not understand how much resource is needed to support each of their application workloads, and in order to maintain the service levels, they could only resort to over-provisioning, thus under-utilizing and wasting their cloud resources. With the application workload metrics collected by Datadog, our enterprise customers want to turn such information into actionable insights – how to determine the right amount of cloud resources at the right time to support each of their many applications, each with different workloads and service-level requirements. This is not a task that an enterprise IT team... --- - Published: 2019-10-24 - Modified: 2020-09-04 - URL: https://prophetstor.com/2019/10/24/democratizing-cloud-usage-with-digital-intelligence-for-multicloud/ - Categories: blog - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat Target Audience: Users of NetApp Kubernetes Services Desired Action After Reading Post: Sign up for free trials. Topic – How NetApp Kubernetes Services users benefit from using Fderator. ai from ProphetStor Keywords: NetApp NKS, Kubernetes Management, MultiCloud, Day 1 Operation, Day 2 Proactive Management helps to boost performance and reduce cost in moving to Public CloudsOperation OutlineProactive Management helps to boost performance and reduce cost in moving to Public Clouds Microservices, Kubernetes, and MultiClouds are winning. They also create issues that need to be addressed for universal acceptance. Cloud helps free the developers and data scientists from operating in the legacy IT infrastructure so they can focus on developing quickly, deploying easily, and adding values to differentiate the company from others. Life was easier in the days when there is only one cloud service provider. Nowadays, the developers need to release on other public clouds, dealing with the difference among clouds, and it becomes a big hassle. Microservices are wining, and Kubernetes is wining. However, as putting together release strategies, building microservices, and support Kubernetes services on MultiClouds becomes a norm, the developers are joggling with the deployment, and they need a service, rather than expensive software, to simplify the task. Anthony Lye of NetApp once said, “We Loved Stackpoint. io So Much, We Had to Buy the Company! ” StackPointCloud takes the complexity out of the deployment of Kubernetes to MultiClouds, including the upcoming NetApp HCI private cloud offering. We consider this a great solution to the Day 1... --- > The fluctuation in creating/deleting Kafka consumers may not be effective and result in added lags (queue length), which is not desirable for the operation. AI/ML-based solution - Published: 2019-10-24 - Modified: 2024-01-15 - URL: https://prophetstor.com/2019/10/24/application-aware-federator-ai-for-kafka-on-kubernetes-enhances-performance-and-reduces-cost/ - Categories: blog - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat Introduction A Kafka Stream Application reads from a topic, Software-Defined Storage performs some calculations, transformations to finally write the result back to another topic. To read from a topic, it creates a consumer. Kafka has become a standard tool to manage a highly loaded streaming system. However, it does not provide mechanisms for dynamic cluster capacity planning and scaling strategies. Scaling the application is about running more of the consumers. Generally, to optimize the consumer processing rate, users may assign the same number of consumers as the number of partitions for related topics. However, using such an Over-Provision policy to allocate consumers may result in unnecessary waste of resources. Hence, there have been works trying to leverage Kubernetes Horizontal Pod Autoscaler (HPA) and hope that the autoscaler can handle the allocation of the right amount of resources at the right time to achieve better utilization of the resources. There are some disadvantages to Kubernetes HPA: Kubernetes HPA combines recommendations (calculating the desired replicas) and executions (adjusting the number of replicas) to set the number of replicas by the HPA controller. However, we have seen more and more operator-based applications in a Kubernetes cluster. Kubernetes HPA is not suitable to auto-scale operator-based applications. And users may need only recommendations and run customized executions separately. If metrics are not chosen appropriately to calculate desired replicas, adverse effects on performance might happen. Users need to take extra care to find a proper metric by trial and error. In this article, we would like... --- - Published: 2019-05-08 - Modified: 2024-01-16 - URL: https://prophetstor.com/2019/05/08/prophetstor-federatorai-operator-provides-intelligence-for-openhift/ - Categories: Press Releases ProphetStor Data Services, Inc. has officially announced its Federator.ai Operator that is listed on OperatorHub.io and can be installed in Red Hat OpenShift Container Platform. BOSTON - Red Hat Summit 2019 - May 8, 2019 —ProphetStor Data Services, Inc. has officially announced its Federator. ai Operator that is listed on OperatorHub. io and can be installed in Red Hat OpenShift Container Platform. ProphetStor’s Federator. ai provides a cost-optimization solution for MultiCloud environments. MultiCloud operations can be split into two categories – Day-1 and Day-2. Day-1 is optimized by Federator. ai sifting through numerous cloud providers and conveniently providing a recommended provider and instance type based on specified application workload requirements. Day-2 is optimized using machine learning to analyze ongoing workload and predict future usage, which can be applied to auto-scalers and schedulers for much more intelligent resource management. The Federator. ai solution helps users to minimize unnecessary costs due to over-provisioning while supporting users’ service requirements for both Day-1 and Day-2 operations. It also helps cloud service providers enhance the agility of their resource management and minimize the cost of resources needed for providing their services. “More and more, we’ve seen enterprise organizations embrace MultiCloud strategies that give them the flexibility to use the right cloud for their needs. By collaborating with ProphetStor, we are excited to offer an advanced AIOps solution on OpenShift that can use machine learning to intelligently optimize both Day-1 and Day-2 operations of MultiCloud environments. ” said Julio Tapia, Director, Cloud Platforms Partners Ecosystem, of Red Hat. “Red Hat is a strong player in providing MultiCloud and open source enterprise solutions. We at ProphetStor are proud to work with Red... --- - Published: 2019-05-03 - Modified: 2024-02-15 - URL: https://prophetstor.com/2019/05/03/prophetstor-will-exhibit-aiops-for-openshift-solution-in-red-hat-summit-2019-in-boston/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent MILPITAS, CA, May 03, 2019 —ProphetStor Data Services, Inc. , the leader in Digital Intelligence for Multi-Cloud platforms is delighted to announce its participation at Red Hat Summit 2019 in Boston and to showcase its latest AIOps for Red Hat OpenShift solution on May 7-9. "Multi-Cloud is the future of IT, and ProphetStor is a game changer," said ProphetStor's CEO Eric Chen. "We are honored to be featured in the Red Hat Keynote sessions that include many prominent industry leaders and enterprise users. We are also delighted to offer to the market the first advanced AIOps solution, Federator. ai® 2. 0 for OpenShift, that has full integration of Red Hat OpenShift 3. 11 and 4. 0 and offers digital intelligence based on our patented AI/Machine Learning technologies for optimizing resource management and user experience in multi-cloud environments. ” Other than the keynote participation, ProphetStor will have a live demonstration of the Federator. ai solution and its use cases in Booth #1134 during the Red Hat Summit Exhibition Hall opening hours. ProphetStor executives and solution architects will be on site to demonstrate the solution and show how it addresses the most urgent issues in multi-cloud, including cost and resource optimization in Kubernetes, and multi-layer visibility. All are welcomed to join us. For the Featured Keynote Speakers in Red Hat Summit 2019, please refer to Red Hat Summit 2019 Keynote speakers. For the detailed specification of Federator. ai for OpenShift, please refer to its datasheet. Start for FREE Tweet About ProphetStor Data... --- - Published: 2019-05-03 - Modified: 2024-01-16 - URL: https://prophetstor.com/2019/05/03/prophetstor-is-granted-a-patent-on-modeling-application-workloads-to-automate-the-management-and-to-predict-the-anomalies-of-storage-resources-in-multicloud-environments-2/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent MILPITAS, CA, May 03, 2019 — ProphetStor Data Services, Inc. , a leader in Digital Intelligence for MultiCloud platforms, was awarded a new patent number US 10,248,332 B2, entitled “A method and system for life expectancy extension of disks in cloud-based service system” by the United State Patent and Trademark Office. The patent is related to applying AI and Machine Learning technologies in optimizing resource management and user experience in MultiCloud environments. This 11th US patents in AIOps (AI in IT Operations) future secure ProphetStor’s leading position in MultiCloud solution offering. Different from finding out why some disks (HDD/SSD) can last longer, this new patent can be applied to find out why some disks (HDD/SSD) can last longer. After studying hundreds of thousands of disks, we have found out the correlation of disk IOPS, latency, and throughput with the host CPU loading and memory usages, and thus specific IO patterns can be applied to disks to prolong their lifespans. Integration of this patent with ProphetStor's other patents helps to deliver a cutting-edge Data Science-driven solution for our AIOps solutions for MultiCloud environment. With the infrastructure intelligence, in addition to provide a platform-based view of the operation, we can at the same time handle multi-layer correlations of the services. As a result, resource management can be better optimized, and the application-level SLA can be best maintained. It will also help the decision of the workload placement in a private cloud or moving to public clouds when needed. Start for FREE Tweet... --- - Published: 2018-10-29 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/10/29/arrow-electronics-extends-data-and-artificial-intelligence-portfolio-with-prophetstor/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent Paris, October 29, 2018 — Global technology provider Arrow Electronics and Intelligent Data Platform provider ProphetStor Data Services, Inc. , have entered a distribution agreement by which Arrow will make ProphetStor`s data intelligent solutions available to channel customers in EMEA. ProphetStor, headquartered in Milpitas, Calif. , provides enterprises and cloud service providers with artificial intelligence-enabled data services. Major IT vendors distributed by Arrow work with ProphetStor on data security protection. The agreement with ProphetStor demonstrates Arrow`s commitment to provide the channel with sophisticated solutions. With Federator. ai®, ProphetStor developed the AIOps platform approach connecting DevOps processes with artificial intelligence. The platform enables DevOp teams to leverage technology for data aggregation, machine learning, visualization and automation. ProphetStor`s flagship product is DiskProphet®, a patented and intelligent data analytics solution that addresses the problem of data loss prevention. The solution continuously collects data from hard and solid-state disks to predict behavior and to provide prescriptive actions. “ProphetStor is another great example for emerging players that Arrow adds to its portfolio when it comes to the key technology trends of tomorrow,” says Alexis Brabant, vice president of sales for Arrow`s enterprise computing solutions business in EMEA. “Both large vendors and new disruptive players are increasingly focusing on the rising artificial intelligence and machine-learning technology. At Arrow, we enable the channel to enter the extremely important market of DevOps data science. ” “We are delighted to work with Arrow in the data-growth market, and continue expanding our global presence in EMEA by bringing intelligence into... --- - Published: 2018-09-24 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/09/24/disk-health-prediction-for-ceph-mimic/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent MILPITAS, CA, September 24, 2018 — We at ProphetStor Data Services, Inc. are excited to announce our contribution to Ceph’s open-source community. Our technology is manifested as the DiskPrediction plugin for Ceph Mimic, and was recently received with great prospect at Ceph Day in Silicon Valley. The DiskPrediction plugin is offered in three different packages – Community On-Premise, Community Cloud, and Commercial Edition. ProphetStor’s disk prediction technology allows users to replace disks at convenient times in their schedule rather than after random occurrences of device failure. This ensures both operational and performance stability is minimally impacted. With this newly added feature, Ceph users are now able to comfortably maintain their cluster before an OSD fails - drastically reducing impeded performance time from rebalancing. Additionally users can preemptively trigger an OSD out on the problem disk, ensuring the cluster always has the appropriate amount of replicas of each storage object. The DiskPrediction plugin supports two modes: cloud and local. In cloud mode, the disk metrics and Ceph information is collected from the cluster and sent to a DiskProphet prediction engine over the Internet. DiskProphet in turn analyzes the data and provides its prediction results of disk performance and health back to the cluster. The accuracy of these results are measured at over 95%. Local mode does not require an external server for data analysis to output results. In this mode, the DiskPrediction plugin uses a light-weight, internal prediction module to provide a less accurate prediction of disks for the cluster. This... --- - Published: 2018-09-21 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/09/21/lanner-partners-with-prophetstor-to-deploy-ai-based-predictive-maintenance-service-for-vcpe-ucpe/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent Lanner Partners with ProphetStor to Deploy AI-based Predictive Maintenance Service for vCPE/uCPE Fremont, USA, September 21, 2018 — Lanner Electronics (TAIEX 6245) the global leading supplier in network communication platforms, announced today its strategic partnership with ProphetStor Data Services Inc. , an Intelligent Data Platform leader, to co-develop an AI (Artificial Intelligence) – based Predictive Maintenance Service for vCPE/uCPE devices. The joint solution offers hardware failure prediction and resource monitoring capabilities enabled by AI technologies, aiming at improving SD-WAN management and maintenance efficiency for ComSPs (communication service provider). The vCPE/uCPE Predictive Maintenance Service engine by Lanner and ProphetStor is aimed to deliver higher standard of QoS (Quality of Service) in SD-WAN deployments. The new solution allows remote management of uCPE/vCPE through one single dashboard, where IT staff is able to manage and monitor the hardware status and lifespan of key components of deployed devices. By integrating ProphetStor AI-driven Data Services technology in Lanner vCPE/uCPE, SD-WAN service providers can not only enable remote management and visibility of the distributed devices status, including CPU, memory, storage disks, but also analyze device system logs and hardware anomalies to prevent potential failure and ensure service availability. . “To accelerate the SD-WAN time-to-market, Lanner is committed to provide the most comprehensive white-box vCPE/uCPE to achieve zero-touch deployment”, said Terrence Chou, General Manager of Lanner USA. “With these integrated solutions, our customers can take proactive actions that addresses problems caused by potential disk failure, reducing hardware maintenance efforts and assuring SD-WAN serviceability. ” To further strengthen... --- - Published: 2018-04-23 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/04/23/prophetstor-announces-its-first-ai-driven-all-flash-array-customer-in-united-kingdom-kennedy-wilson/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor Announces its First AI-Driven All Flash Array Customer in United Kingdom, Kennedy Wilson MILPITAS, CA, April 23, 2018 — ProphetStor Data Services, Inc. , a leader in Intelligent Data Platform, was chosen by Kennedy Wilson Europe, a leading real estate investment company, to provide its next generation All Flash Storage platform. The utilization of storage resources is always a myth to IT managers. There are too many hidden resources and uncertainties when IT managers make a plan to serve their mission-critical applications. Nobody really knows how many IOPS a specific workload needs exactly. Over-provisioning causes the low utilization of storage resources only because of those uncertainties. StellarFlash’s AI engine predicts the demands of workloads through self-learning and analytics, and automatically provides IT manager an adaptive storage resource plan. Mansoor Rahaman, Head of IT for Europe for Kennedy Wilson stated “Selecting the all flash solution for Kennedy Wilson in a crowded market was a challenge. The ProphetStor solution had the speed and price point we required but the built in AI services ensure we have a guaranteed service level for our key applications. ”Guillaume Imberti, EMEA GM at ProphetStor stated “This decision justifies our strategy and investment in Artificial intelligent in the Datacenter. The StellarFlash® All Flash Array’s built in storage optimization technologies ensure market leading performance but at mainstream prices. ”StellarFlash® AFA is supported by a patented analytics service that addresses data loss prevention in a unique way. The service accesses operational data of SSD’s to predict with greater... --- - Published: 2018-04-16 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/04/16/ai-enabled-disk-prophet-paves-the-way-for-intelligent-data-center-operations/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor’s New AI-enabled Disk Prophet™ Paves the Way for Intelligent Data Center Operations MILPITAS, CA, April 16, 2018 — ProphetStor Data Services, Inc. , a leader in Intelligent Data Platform, announced today the availability of an updated version of StellarFlash® 5. 0 (build # 3093), a flash-optimized storage software that powers both of All-Flash Arrays (AFA) and Hybrid Arrays solutions. StellarFlash® now integrates with the latest version of Disk Prophet™ 2. 5; its patented intelligent data analytics and predictive engine for disk failure, fault, and fatigues. The new capabilities of predictive analytics and intelligent operations improve the SLAs of Software-Defined Data Centers (SDDC) with much reduced cost and uncertainty. StellarFlash® not only has optimized performance, but also becomes proactive and intelligent. The integration improves operational efficiency as it helps customer act upon the disk failure predictions to decide the best time for disk replacement without performance degradation and service outage. ProphetStor is committed to introducing innovative solutions for bringing intelligence into Software-Defined Data Centers. The details of both releases as well as the new features associated with the releases are described below:Key Features of StellarFlash® 5. 0 includes: Disk Prophet™ integration provides disk failure prediction and volume/pool/disk impact analysis with enhanced user interfaces and experiences. Advanced configuring for including NVMe as cache for appliances. Key Features of Disk Prophet™ 2. 5 includes:Correlation analysis in vSAN environment: Disk Prophet™ provides a comprehensive data and resources analysis in a vSAN environment. DiskProphet™ automatically detects the entities, such as VMware hosts, datastores, VMs,... --- - Published: 2018-04-14 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/04/14/prophetstor-partnership-with-peering-one/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent KUALA LUMPR, MALAYSIA, April 03, 2018 — ProphetStor Data Services, Inc. , a leader in Intelligent data platform, today announced a strategic alliance with Peering One, a leading enterprise cloud provider in APAC, to integrate StellarFlash® in their Storage-as-a-Service (STaaS) business model, providing the ultimate path to self-driving data centers. The STaaS is house to array of customer data inclusive of Production workloads, Virtual machines, Private cloud and Disaster Recovery. The partnership was aimed to meet enterprise-class data center customers’ needs for high Quality of Service (QoS) with Pay-Per-Use (PPU) model. The complexity of customer’s data center experience has resulted in an increased demand for efficient and reliable data services. The bottleneck in delivering an unprecedented user experience for digital services today is not down to processing power but is because of storage. While Solid State Disks (or better known as SSDs) offer significant improvements in storage performance, they are still expensive and a mere pipedream for many. StellarFlash® is a storage array that takes advantage of SSDs to allow cloud providers like Peering One to deliver the best user experiences possible in helping customers achieve assured QoS with a service-driven model. This STaaS service is hosted at Peering One’s data centers; being the first data centers in Malaysia and second data center in APAC to secure a Tier III Design Certification by the Uptime Institute. Tier III Certification is awarded to data centers with the highest reliability and availability level. “A combined solution from ProphetStor and Peering One can... --- - Published: 2018-02-27 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/02/27/ai-driven-diskprophet2-0/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor’s AI-Driven DiskProphet® 2. 0 Leaps to Deliver Higher Standard of Services with Accurate Predictions for Both Disks and Systems MILPITAS, CA, February 27, 2018 — ProphetStor Data Services, Inc. , a leader in Intelligent data platform, announced today the general availability of its patented intelligent data analytics and predictives solution for disk failures – DiskProphet® 2. 0, now with expanded platforms and enhanced GUI for DiskProphet Server and DiskProphet. com Cloud Services. The DiskProphet® 2. 0 release features several new capabilities and enhancements that addresses the challenges of software-defined datacenters: Impact analysis with total visibility of correlation of virtualizations. A resource map is built from a hierarchical structure of VMware’s objects by collecting metadata from vCenter. With this structure, DiskProphet helps users quickly identify virtual machines and datastores that are affected by a predictive disk failure. Workload prediction and optimization. Prediction of physical hosts and virtual machines workload by using the advanced machine learning technology improves infrastructure resource utilization and reduces performance conflicts. The highlight of this new release is the support of VMware vSAN. DiskProphet® 2. 0 predicts the failure of the disks installed in ESXi hosts of a vSAN cluster. The users of Hyper-Converged Infrastructure (HCI) usually suffer from significant performance degradation during the time vSAN data re-balancing started due to a disk failure. With DiskProphet’s disk failure and performance prediction capabilities, the data center operation can proactively prevent the impact of disk failures in a virtualization environment. Key Features of DiskProphet® 2. 0 includes:Provides REST API... --- - Published: 2018-01-16 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/01/16/workload-consumed-resource-management-in-a-cloud-data-center/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor Strengthens Its Global Patent Portfolio with AI-enabled Predictives for Optimizing Utilization of the Workload-Consumed Resource Management in a Cloud Data Center MILPITAS, CA, January 15, 2018 — ProphetStor Data Services, Inc. , a leader in Intelligent data platform, today announced that it has been assigned a new US patent that is essential to system management towards optimization of resource planning and allocation with predictives in the cloud data centers of any sizes. The U. S. Patent and Trademark Office (“USPTO”) assigned United States Patent number 9,852,009 to ProphetStor. This patent, entitled ”Method for Optimizing Utilization of Workload-Consumed Resources for Time-Inflexible Workloads,” helps ProphetStor Federator. aiTM to be able to combine intelligently, with predictives, multiple workload-consumed resource profiles with the support of QoS. With the technology, the resource allocation and planning decision for the future can be made at the current time with the insight of the past and the predictives for the future. As a result, it relieves the heavy workload for the cloud operator in pursuit of cost-effective, efficient resource sharing operation. Key features and benefits of this technology include:Computational resources saving with fulfillment of SLAs. Optimization of VMs/Containers-Consumed Resource Utilization. Management of VMs/Containers placement and migration. Green solution toward to environment sustainable computing. “As a leading-edge Intelligent Data Platform company, we continually to innovate in AI-driven solutions for self-driving data centers technology to ensure our customers, while adopting software-defined solutions to their data centers, can still grow their businesses and operate their cloud data centers with confidence,”... --- - Published: 2018-01-04 - Modified: 2024-01-16 - URL: https://prophetstor.com/2018/01/04/prophetstor-patent-aims-to-simplify-ai-driven-container-intelligence-for-self-driving-data-center/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor Patent Aims to Simplify AI-Driven Container Intelligence for Self-Driving Data Center MILPITAS, CA, January 04, 2018 — ProphetStor Data Services, Inc. , the leader in software-defined storage (SDS) and data services solutions, was awarded a new patent number US 9,817,584 B2 by the United State Patent and Trademark Office, relates to storage system having a node with light weight container in Software-Defined Data Center (SDDC) solutions. Container technology are changing the dynamics for data centers. A data center can easily have tens of thousands to millions of containers, it is impossible for IT administrators to handle the resource configuration, health status and meet Service Level Agreements (SLAs) at the same time. This new patent doesn’t only describe the automation mechanism of container operation by AI, but also includes a clear and holistic design for an AI-driven container intelligence. It carefully puts the different roles of containers into consideration. It illustrates the automation of three types of containers that are commonly seen in a data center. They are storage containers to operate the storage device, data containers for running databases, and application containers for providing the specific service. “Integration of this patent with other ProphetStor’s patents helps to deliver a cutting-edge AI-driven solution for a self-driving data centers. With the container intelligence, it can automatically manage the operation of containers without human intervention. It will decide when to add more containers to hosts or remove containers from the hosts based on the prediction that’s available from computing resources, detected anomaly... --- - Published: 2017-12-01 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/12/01/xsky-and-prophetstor-team-up-in-strategic-partnership-in-beijing/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent BEIJING, CHINA, December 1, 2017 — XSKY Beijing Data Technology Corporation Limited and ProphetStor Data Services, Inc signed a strategic partnership agreement in Beijing that enhances XSKY’s position in the storage market, while significantly expanding ProphetStor’s reach in China with a joint solutions using DiskProphet to improve the reliability and overall efficiency of the Ceph system. XSKY Beijing Data Technology Corporation Limited focus on Software Defined Infrastructure. XSKY products and solutions are mainly based on Ceph, which is #1 open-source software-defined-storage system in this market. With this combined solutions, end user will get a non-lock-in solution and their investments are protected. Based on open-source, XSKY adds on enterprise-ready interfaces and 24 by 7 maintenance capability to support generic Ceph. XSKY helps customer reduce total cost of ownership and solve their dilemma in managing data growth with minimal budgets. ProphetStor Data Services, Inc. , a leader in Software-Defined Storage (SDS), provides federated storage solutions to enable data centers to provide a more agile, automated, and intelligent storage infrastructure orchestration platform that is applicable to both enterprise and cloud services data centers. The new partnership is expected to inspire innovation and promote the intelligent disk life prediction solution – DiskProphet with integrated support structure to meet the industry standard of storage solutions. XSKY and ProphetStor working to continue to grow the enterprise customers to adopt the next-generation intelligent data analytics solution that addresses the problem of data loss prevention in a unique way. Start for FREE Tweet About ProphetStor Data Services, Inc.... --- - Published: 2017-09-18 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/09/18/stellarflash-arrays-delivers-intelligence-to-software-defined-datacenter/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent To Satisfy the Changing Needs of Business-Critical Applications MILPITAS, CA, September 18, 2017 — ProphetStor Data Services, Inc. , the leader in software-defined storage solutions, announced today the availability of the StellarFlash Arrays based on certified commodity storage server platforms. The turnkey appliances are available in an all-flash-array (AFA) configuration or as a hybrid (HFA), combination of both SSDs and hard disks offering a blend of capacity and performance. StellarFlash integrated with ProphetStor’s patented analytics, machine learning with Artificial Intelligence (AI) and prediction services, ensures that all resources are monitored and any disruption due to wear/tear is caught via predictive analytics early on to prevent unforeseen downtime. This was made possible by combining high-performance arrays with built-in software-defined storage and data services along with data protection and recovery services. “ProphetStor’s StellarFlash arrays help companies stay ahead of storage and application demand for growth and performance in a cost-effective manner," said Eric Chen, ProphetStor CEO. “This is an ideal form factor for the channel and OEM partners, which we are actively recruiting around the globe to enable them to offer the benefits of Federator SDS within this all flash or hybrid appliance. Our customers will have a virtualized solution that is highly intelligent, flexible and aware, and specifically built to address their storage, application and data protection needs today and in the future. ” StellarFlash Storage Arrays comes with VMware Storage Hardware Certification including VAAI Block Devices to ensure customers obtain a jointly certified and supported hardware solutions. StellarFlash is also... --- - Published: 2017-09-15 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/09/15/prophetstor-germany-go-to-market-with-delivering-intelligence-to-software-defined-datacenter/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent First Appearance in Cloud 2017 Technology and Services Conference in Munich, Cologne and Hamburg PARIS, FRANCE. , September 15, 2017 – ProphetStor Data Services, Inc. , the leader in software-defined storage (SDS) and data services solutions, is pleased to announce its first participation at the Cloud Technology and Services Conference for end-users and channel partners across 3 cities in Germany (Munich, Cologne and Hamburg) since its branch office established recently to build a customer base, channel partners, OEMs and engage with cloud providers in Central and Eastern Europe. “In this three-location conference, we are excited to showcase ProphetStor’s patented artificial intelligence technologies leverages the industry-leading open source cloud computing platform OpenStack and integrates it with our state-of-the-art software-defined-storage Federator® SDS to offer organizations a complete package of software-defined datacenter with a host of sophisticated data services, in a very cost-effective fashion,” said Guy Berlo, Vice President of Central Europe, ProphetStor. As part of go-to-market strategy, this conference is the company’s first customer and channel-focused event in the area and is expected to attract total of 500 attendees from the public sector, finance institution, insurance, telco, and manufacturing. ProphetStor will be participating in World Cafés to exchange views and experiences on cloud solution. Attendees will also have the opportunity to experience cutting edge cloud-based solutions and services from many of the industry’s top cloud vendors, cloud service providers, and ISVs. Start for FREE Tweet About ProphetStor Data Services, Inc. ProphetStor Data Services, Inc. , a leader in the Intelligent Data Platform,... --- - Published: 2017-08-09 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/08/09/prophetstor-announces-distribution-agreement-with-info-x-distribution-to-promote-ai-empowered-stellarflash/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent The new distribution agreement is expected to strongly expand ProphetStor’s presence in North America MILPITAS, CA. , August 09, 2017 – ProphetStor Data Services, Inc. , the leader in software-defined storage (SDS) and data services solutions, today announced it has signed a distributor agreement with Info X Distribution, a technology distributor specializes in the distribution of storage, software, and server connectivity of virtualized networks and cloud environments. With ProphetStor’s artificial intelligence (AI) empowered flash technologies and Info X’s global channels of storage products, both companies team up to deliver StellarFlash to customers. StellarFlash appliances are available in all-flash-array (AFA) configuration that delivers unprecedented user experiences or as a hybrid combination of both SSDs and hard disks offering a blend of capacity and performance. With the StellarFlash, digital business services are given a new lease of life. “The storage industry is going through a massive transition, which is being caused by flash. StellarFlash help companies stay ahead of storage and application demand for growth and performance in a cost-effective manner,” explained Eric Chen, CEO of ProphetStor. “This agreement will provide ProphetStor with presence in all major cities and access to a wide partner network of over 2000 VARs, VMware Resellers, OEMs and System Integrators. ” Tom Carlucci, President of Info X, added, “As a leading IT global distributor, we are always seeking ways to enhance our portfolio and further empower our partners to offer AI-empowered flash optimized storage solutions to satisfy changing needs of their end-customers. The synergies between our companies... --- - Published: 2017-07-11 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/07/11/prophetstor-drives-emea-expansion-with-key-strategic-appointments-in-france-uk-and-germany/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent Next phase of company’s aggressive expansion strategy kicks off with the opening of EMEA offices with key appointments of Guillaume Imberti as Executive Vice President and General Manager, Thomas Barrett and Guy Berlo, respectively Vice Presidents of North EMEA and Central EMEA to drive growth by focusing on EMEA markets MILPITAS, CA. , July 11, 2017 – ProphetStor Data Services, Inc. , a leader in software-defined storage (SDS) and data services solutions, today announced further expansion into Europe, Middle East and Africa (EMEA) with the opening of its headquarters in Versailles, France to drive localised sales and marketing efforts across two other subsidiaries in the UK and Germany. “We’re excited to continue growing our global presence by establishing roots in Europe, where many leading industries are embracing new technologies to modernize their IT infrastructure,” said Eric Chen, CEO of ProphetStor. “ProphetStor is currently experiencing rapid growth in US and Asia; and with Guillaume Imberti’s leadership and 25 years’ experience in the enterprise data storage industry, we’re looking forward to similarly rapid growth in EMEA. The new establishment will provide sales and pre-sales support, customer service and technical assistance to customers and partners. ProphetStor SDS technology brings intelligence into the data center and cloud infrastructure, and provides orchestration, analytic, prediction, and resource automation capabilities that greatly enhance the efficiency of managing data centers. “ProphetStor recognizes the importance of the EMEA marketplace,” said Guillaume Imberti, Executive Vice President and General Manager, ProphetStor EMEA. “Europe is full of enterprise and mid-market businesses that... --- - Published: 2017-05-29 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/05/29/data-security-solutions-to-safeguard-against-ransomware-by-hpe-prophetstor-innovix/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor and Innovix Distribution to introduce the Latest Innovation of Data Security to Safeguard against Ransomware MALAYSIA, KUALA LUMPUR, May 29, 2017 – ProphetStor Data Services, Inc. , the leader in software-defined storage (SDS) and data services solutions, in collaboration with Innovix Distribution (Innovix) used solutions from Hewlett Packard Enterprise (HPE) to develop an effective and reliable new data security system to combat ransomware. The data security system is now available, and aims to combat ransomware and help enterprises avoid suffering heavy losses in revenue over the years. The ProphetStor DR Prophet® Software-Defined Data Protection is a powerful anti-ransomware software with the ability to recover any file, folder, disk and even entire servers from being hijacked or stolen and restore them to the original state. This new innovative software is powered by the robust and cost-effective HPE ProLiant ML10 Gen9 server and HPE ProLiant ML30 Gen9 server, which enables cost-conscious customers to reap the benefits from an all-in-one solution bundle. This anti-ransomware solution bundle is unique because it can provide Assured Recovery and Enhanced Protection Policy to safeguard against ransomware, which means that customers can achieve full server recovery up to the last snapshot stored within minutes. Customers who sign-up for the ProphetStor DR Prophet Software-Defined Data Protection bundle will be provided with hardware, storage, protection software and a virtual standby recovery server – making it one of the most affordable All-In-One (AIO) solution bundles to safeguard against ransomware in the market. This innovative solution bundle is tailored for small... --- - Published: 2017-05-22 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/05/22/dr-prophet-safeguards-enterprises-against-ransomware/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent ProphetStor DR Prophet® Safeguards Enterprises against Ransomware with Assured Recovery and Enhanced Protection Policy MILPITAS, CA, May 22, 2017 – ProphetStor Data Services, Inc. , the leader in software-defined storage (SDS) and data services solutions, today announced it has technologically advanced and reliable first-hand data protection solution at combating ransomware. The ProphetStor DR Prophet® Software-Defined Data Protection is a powerful anti-ransomware software with the ability to recover any file, folder, disk and even entire servers from being hijacked or stolen and restore them to the original state. Nowhere is it more true that “An ounce of prevention is worth a pound of cure,” than in the case of Ransomware. It’s more prudent to head off a disaster beforehand than to deal with it after it occurs. ProphetStor DR Prophet® is irreplaceable because it can provide Assured Recovery and Enhanced Protection Policy to safeguard against ransomware, which means that customers can achieve full server recovery up to the last snapshot stored within minutes. “ProphetStor’s strategic business proposition to customers is to take a close look at their data protection and disaster recovery practices for current and transitioning environments as we see the significant increase of customers targeted by ransomware or other cyber-attacks,” said Eric Chen, ProphetStor CEO. “The recent ransomware ‘WannaCry’ attack on Friday, 12 May 2017, infecting more than 230,000 computers in 150 countries, and the ransomware takes over users’ files, demanding a ransom to restore them. ” “The message from the UK’s National Crime Agency was “do not pay!... --- - Published: 2017-02-17 - Modified: 2024-01-16 - URL: https://prophetstor.com/2017/02/17/ai-holdings-invested-us10-million-to-expand-business-in-japan/ - Categories: Press Releases - Tags: 5G, AI, AIOps, ApplicationAware, Datadog, GreenIT, Kubernetes, MachineLearning, MultiCloud, OpenShift, RedHat, USAPatent Ai Holdings Corporation Makes US$10 Million Investment and Joins Forces with ProphetStor to Expand Business in Japan ProphetStor Data Services, Inc. , the leader in software-defined storage (SDS) and data services solutions, today announced it has signed an exclusive distributor agreement with Ai Holdings Corporation, a Japan-based IT provider, to collaborate on product resale, and offer service and maintenance support of next-generation storage solutions to customers in Japan. ProphetStor offers integrated multi-use storage systems while enabling the use of commodity servers, by leveraging existing storage and application investments and taking advantage of the future storage investments involving all-flash and big data environments. Its global patent portfolios create the next wave of SDS technology, bringing intelligence into the data center and cloud infrastructure, and providing orchestration, analytic, prediction, and resource automation capabilities that greatly enhance the efficiency of managing data centers. “Partnering with Ai Holdings adds a great depth and wider reach to our localization and business development efforts in Japan,” said Eric Chen, ProphetStor CEO. “Global expansion is important to us. With this excitement, we are jointly developing plans to build customer awareness and market momentum for rapid adoption of scalable storage and data services management for data centers customers. ” “As a leading distributor, we see the level of activities and overall adoption rate of some of the latest Internet of Things (IoT) and Big Data technologies in Japan makes us very motivated to work with ProphetStor,” said Hideyoshi Sasaki, CEO of AI Holdings Corporation. “With ProphetStor’s industry-proven and... --- ---