Tag: GreenIT

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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“ (Patent number US 10,013,286) by the United States Patent and Trademark Office.

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ProphetStor’s 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 number US 10,067,704) by the United States Patent and Trademark Office.

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ProphetStor’s Patent on AI-Powered Workload-Aware Framework Becomes the Foundation of AIOps for Optimization in MultiCloud and 5G

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.

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Orange France Uses Federator.ai for Auto-scaling, Optimizing Resources and Application Performance on Its MultiCloud Infrastructure

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.

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Federator.ai – AI Solution for Auto-Scaling on Kubernetes with Datadog

With Datadog, our enterprise customers are now able to monitor their application workloads and get visibility into Kubernetes clusters of any scale. The new integrationbetween 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

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Application-Aware Federator.ai for Kafka on Kubernetes Enhances Performance and Reduces Cost

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

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