StormForge Optimize
StormForge
StormForge Optimize
StormForge
StormForge Optimize
StormForge
StormForge automates Kubernetes resource efficiency at scale using machine learning
Inefficient Kubernetes and application configurations result in millions of dollars in wasted cloud resources, business-impacting performance and availability issues, and thousands of hours of lost productivity every year.
StormForge is the only optimization platform that solves the Kubernetes efficiency challenge holistically, with both proactive optimization in non-production environments and continuous optimization in production using observability data.
Ensure applications work efficiently before deployment, and keep them running efficiently in production.
StormForge Optimize is designed for:
- Business and Technology Leaders Focused on Saving Time and Money
- Cloud Operations Professionals and Developers Charged with Ensuring Application Performance and Resiliency
- Application Owners Driving New Features That Accelerate Your Competitive Advantage
Predictive scenario analysis to understand and optimize applications before deployment
In pre-production, StormForge Optimize Pro uses rapid experimentation to optimize for every possible scenario and provides in-depth application analysis and insights to drive key architectural improvements.
- In-depth application insights for driving improvements in cloud native architecture
- Integrated performance testing and optimization in a single platform
- Maximum flexibility with ability to optimize for any metric
Turn observability into actionability with continuous optimization of your cloud native prod environment
In production, StormForge Optimize Live maximizes the value of your existing data and tools to reduce resource usage and cost while still meeting SLAs. StormForge accelerates your competitive advantage by allowing developers to focus on innovating, not tuning Kubernetes.
- Improved efficiency compared to VPA thanks to advanced ML
- Tune applications using existing telemetry
- Confidently deploy recommendations with automatic or manual approval