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Federator.ai®

Why Needs An AIOps Tool

If your operations are facing these challenges, you need to check out our AIOps solution Federator.ai no matter which phase of the cloud 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 future

  • To integrate cloud-based platforms to solve business problems rather than solving the integration itself

  • To 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 operations

  • To 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 involved

  • To 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 demands

Benefits of Federator.ai

Federator.ai integrates with the existing monitoring services and adds values to the collected operation metadata to proactively resolve operation resource issues before they become problems. It 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 both cost-effective resource allocation and application resilience without adding extra skilled architects and operation personnel.

Moreover, the constant bidirectional connectivity between actual IT operations and its Digital Twin, which mirrors the infrastructure and applications running on it, provides precise predictions and recommendations based on the characteristics of different applications, and, eventually, reinforces a virtuous cycle of optimization for both operational performance and cost savings. 

The value propositions of Federator.ai

Operation Simplicity

Federator.ai reduces the complexity of operation by up to 80%. One installation of Federator.ai manages multiple clusters (Kubernetes/ OpenShift/ VM cluster) and application in a hybrid cloud/ MultiCloud environment.

Performance Resilience

With Just-in-Time Fitted recommendations from our patented DataProphet Recommendation Engine, application performance and resilience can be ensured with automatic and agile resource adjustments, without human errors or ingenuity.

Cost Optimization

The overall cost saving in Cloud operations with Federator.ai ranges from 35% up to 90%, according to field experience. The savings include minimizing idle resources, selecting the most cost-effective instance types, and choosing the best purchasing models from cloud service providers.

Key Features of Federator.ai

Federator.ai’s one Single-pane-of-glass management console locally and remotely manages clusters in a Kubernetes environment, no matter the resources deployed in private, public, hybrid cloud, or MultiCloud. The AI-based engines (CrystalClear Time Series Analysis Engine and DataProphet Recommendation Engine) of Federator.ai dynamically predict resource consumption and recommend the right amount of resources for pods that accurately match the workload, and, therefore, optimizes costs for both Day-1 deployment and Day-2 operations.

Applications

mongo DB
redis logo
PostgreSQL Logo

Metric Data Sources

Federator.ai taps into monitoring services like Prometheus and application accelerators like Kafka to optimize costs for Day-1 deployment and Day-2 operations on MultiCloud.