Kubernetes Cost Governance: Policies That Stop Waste Before It Ships
Blog post from Cast AI
In the context of Kubernetes cost governance, the overprovisioning of CPU and memory resources is a significant issue, with reports indicating that by 2026, 69% of clusters will be CPU-overprovisioned. Traditional cleanup campaigns have proven ineffective as they fail to address the structural causes of such inefficiencies. Instead, the implementation of policies, such as ResourceQuotas and LimitRanges, is recommended to enforce consumption limits at both the namespace and container levels. These policies are crucial in preventing unnecessary resource consumption by setting predefined boundaries and blocking non-compliant configurations before they are deployed. Tools like Kyverno and OPA Gatekeeper assist in enforcing these policies by validating and mutating resources at admission time. Furthermore, shift-left tooling, such as Conftest and Kyverno CLI, is advocated to catch policy violations during the pull-request phase, significantly reducing costs and ensuring compliance from the earliest stages of the development workflow. Cast AI further enhances governance by rightsizing requests and limits based on actual workload behavior, thereby addressing inefficiencies that policies alone cannot rectify. This comprehensive approach to cost governance emphasizes fixing the underlying processes rather than merely rectifying numerical discrepancies.
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