Optimize Live

Guide to StormForge Optimize Live Tool

Introduction to StormForge Optimize Live

StormForge Optimize Live applies machine learning to your existing observability metrics to make real-time, actionable recommendations to resource settings for any deployment running in Kubernetes. Save cloud resources and money, reduce the business risk of poorly performing applications, and get your developers focused on innovating, not tuning your Kubernetes environment.

Observation-based Optimization

StormForge Optimize Live leverages the observability data you’re already collecting, using machine learning to find opportunities to reduce cloud resource usage and cost while minimizing risk of CPU throttling or out-of-memory errors. Based on historical usage and performance metrics, Optimize Live delivers a continuous, intelligent, and automated approach to maintaining Kubernetes efficiency in production.

Fast Time to Value

Taking only minutes to configure, StormForge Optimize Live can start delivering value for your enterprise today. Specify how frequently you want to see new recommendations, your tolerance for risk, and whether you want to automatically implement or manually approve recommendations, and you’re good to go. Optimize Live will immediately start analyzing your Kubernetes production environment and find ways to save.

Confidently Deploy Recommendations

As StormForge machine learning makes recommendations, you can choose to put your operations on autopilot by automatically accepting and implementing changes in production, or you can choose to manually approve. Risk tolerance can also be set to low, medium, or high for each application, so you can treat mission critical apps more conservatively, for example. With StormForge, you’re always in full control.

Architecture

StormForge Optimize Live is composed of three parts:

  1. The StormForge Optimize Live Controller, which runs on your cluster,
  2. stormforge, a CLI tool for installing the Controller, and
  3. An API that automatically generates recommend configurations for your application.
Last modified February 22, 2022