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The ProphetStor Federator.ai Cluster Overview dashboard displays resource usage predictions and recommendations for Kubernetes clusters and nodes and historical usage.

The ProphetStor Federator.ai Application Overview dashboard displays predicted CPU and memory usage and recommendations for each application.

The ProphetStor Federator.ai Kafka Overview dashboard displays usage information and recommendations about autoscaling Kafka consumer replicas.

The ProphetStor Federator.ai Cost Analysis Overview dashboard shows deployment cost of a Kubernetes cluster and recommendations of cluster configuration and estimated cost/savings when it is deployed on public cloud service providers.

Federator.ai dashboard displays workload prediction and resource recommendations for Kubernetes or VM clusters and applications.

Federator.ai provides predictions and resource recommendations for clusters, nodes, namespaces, applications, and controllers

Based on predicted workload of a cluster, Federator.ai recommends most cost-effective cluster configuration for different public cloud provider.

Federator.ai analyzes and projects cost trend for individual namespace.

Overview

ProphetStor Federator.ai is an AI-based solution designed to enhance computing resource management for Kubernetes and Virtual Machine (VM) clusters. With its holistic observability of IT operations, including multi-tenant Large Language Model (LLM) training, resources for mission-critical applications, namespaces, nodes, and clusters can be efficiently allocated, and KPIs can be effectively achieved with minimum resource wastage.

• AI-based workload prediction for containerized applications in Kubernetes clusters, as well as VMs in VMware clusters, Amazon Web Services (AWS) Elastic Compute Cloud (EC2), Azure Virtual Machine, and Google Compute Engine
• Intelligent resource recommendations from application-aware workload predictions produced by AI engines after digesting the operational metrics
• Automatic provisioning of CPU/memory for generic Kubernetes application controllers/namespaces
• Automatic scaling of Kubernetes application containers, Kafka consumer groups, and NGINX Ingress upstream services
• Optimal MultiCloud cost analysis and recommendations based on workload predictions for Kubernetes clusters and VM clusters
• Actual cost and potential savings based on recommendations for clusters, Kubernetes applications, VMs, and Kubernetes namespaces
• MultiTenant LLM training observability and actionable resource optimizations without performance compromise

ProphetStor Federator.ai provides full-stack observability through its APIs integrated with Datadog Agents, from application-level workloads, including LLM training, to cluster-level resource consumption. This integration fosters a dynamic loop between live monitoring and predictive analytics, continuously improving resource management, optimizing costs, and ensuring efficient application operation. With a ProphetStor Federator.ai license, you can apply an AI-based solution to track and predict the resource usages of Kubernetes containers, namespaces, and cluster nodes to make the right recommendations to prevent costly over-provisioning or performance-impacting under-provisioning. 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).

Separate from this Federator.ai license, an official Datadog Integration with out-the-box dashboards and recommended monitors is available. For additional information on Federator.ai, you can view the ProphetStor Federator.ai Feature Demo video.

Support

For support or requests, contact ProphetStor support.

This application is made available through the Marketplace and is supported by a Datadog Technology Partner. Click Here to purchase this application.