Kubernetes Cost Optimization: Rightsizing, Resource Efficiency, and Waste Reduction

Calendar February 21, 2026
Kubernetes
Intermediate
Cost-Analysis, Resource-Sizing, Capacity-Planning, Cluster-Optimization
Cost-Optimization, Rightsizing, Resource-Requests, Kubecost, Vpa, Goldilocks, Karpenter, Cluster-Autoscaler, Finops
Kubectl, Prometheus, Grafana, Kubecost, Goldilocks, Karpenter

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.

Vertical Pod Autoscaler (VPA): Right-Sizing Resource Requests Automatically

Calendar February 21, 2026
Kubernetes
Intermediate
Autoscaling-Configuration, Resource-Sizing, Capacity-Planning
Vpa, Autoscaling, Resource-Requests, Right-Sizing, Vertical-Scaling, Goldilocks
Kubectl, Helm, Goldilocks

Vertical Pod Autoscaler (VPA)#

Horizontal scaling adds more pod replicas. Vertical scaling gives each pod more (or fewer) resources. VPA automates the vertical side by watching actual CPU and memory usage over time and adjusting resource requests to match reality. Without it, teams guess at resource requests during initial deployment and rarely revisit them, leading to either waste (over-provisioned) or instability (under-provisioned).

What VPA Does#

VPA monitors historical and current resource usage for pods in a target Deployment (or StatefulSet, DaemonSet, etc.) and produces recommendations for CPU and memory requests. Depending on the configured mode, it either reports these recommendations passively or actively applies them by evicting and recreating pods with updated requests.