Rightsizing Kubernetes Apps and Optimizing Resources at Any Scale with StormForge ML

Cloud waste and operational inefficiency are significant Kubernetes problems that span pre-production, day 2 operations and beyond. The chronic inability to rightsize application resources in complex Kubernetes environments leads to excessive – yet ineffective – manual tuning, gross over-provisioning and unpredictable performance. These outcomes steal time from engineering innovation, generate unnecessarily high cloud costs and create performance and availability risks that degrade the user experience.

This session provides an overview of the StormForge platform, which uses patent-pending machine learning to drive intelligent insights and automatically rightsize Kubernetes resources at any scale. StormForge uses rapid experimentation and scenario analysis to optimize non-production environments and leverages existing observability data to optimize production. The benefits are significantly lower administrative effort and cloud costs, and more predictable SLAs.

Presented by Brian Likosar, Director of Global Solutions Architecture, StormForge.

StormForge Demo: www.stormforge.io/request-demo/

StomForge Free Trial: www.stormforge.io/try-free/