Diagnose & Resolve Risks to Cost & Performance in Kubernetes
What’s putting your K8s workloads at risk
? You probably didn’t immediately think of memory and CPU resources—yet, these pose significant threats to cost and performance in your public cloud Kubernetes and OpenShift deployments, precisely because they are almost always
configured sub-optimally—and often, completely overlooked. Potential impacts of resource misconfiguration include:
- Pod termination by the Kernel OOM process when resources are under-allocated
- Performance degradation, latency, and unresponsive nodes when pods are not limited
- Stranded resources (and wasted spend) when requests for memory and CPU are larger than necessary
Watch this demo as we detail 12 risks across cost and performance, demonstrate a way to visualize the spread of risk in your containers deployment, and present a methodology for drilling down to individual misconfigurations and resolving them.