Kubernetes Cost Optimization#

Most Kubernetes clusters run at 15-30% actual CPU utilization but are billed for the full provisioned capacity. The gap between what you reserve and what you use is pure waste. This article covers the practical workflow for finding and eliminating that waste.

The Cost Problem: Requests vs Actual Usage#

Kubernetes resource requests are the foundation of cost. When a pod requests 4 CPUs, the scheduler reserves 4 CPUs on a node regardless of whether the pod ever uses more than 0.1 CPU. The node is sized (and billed) based on what is reserved, not what is consumed.

Managed Kubernetes vs Self-Managed#

The fundamental tradeoff is straightforward: managed Kubernetes trades control for reduced operational burden, while self-managed Kubernetes gives you full control at the cost of owning everything – etcd, certificates, upgrades, high availability, and recovery.

This decision has cascading effects on team structure, hiring, on-call burden, and long-term maintenance cost. Choose deliberately.

Managed Kubernetes (EKS, AKS, GKE)#

The cloud provider runs the control plane: API server, etcd, controller manager, scheduler. They handle patching, scaling, and high availability for these components. You manage worker nodes and workloads.