Kubernetes Cost Optimizer

Cut Kubernetes cloud bills by comparing pod resource requests and limits against real usage. Find overprovisioned workloads, generate right-sizing recommendations, spot idle capacity, and tune requests/limits for efficient, stable clusters.

This skill analyzes Kubernetes cluster efficiency to reduce cloud spend. It compares configured CPU/memory requests and limits against observed usage from metrics, flags overprovisioned and throttled pods, recommends right-sized requests and limits, surfaces idle nodes and unschedulable waste, and models savings from bin-packing and autoscaler tuning. It also covers VPA/HPA guidance, namespace-level cost breakdowns, and prioritizing the highest-impact workloads to fix first.

When to use

Use when reducing Kubernetes costs — analyzing pod requests vs actual usage, finding overprovisioned or throttled workloads, right-sizing requests/limits, or cutting cloud bills for K8s clusters.

Examples

Right-size overprovisioned pods

Requests vs actual usage

Analyze my deployment's CPU and memory requests against the last week of usage and recommend right-sized requests and limits, flagging any pods being CPU-throttled

Find cluster waste

Idle capacity and savings

Review my namespace's resource allocation, identify idle and overprovisioned workloads, and estimate the monthly savings from applying right-sizing and enabling the cluster autoscaler