Skip to main content
Download free report
SoftBlues
Back to Blog
Gemini & Google Cloud AI
January 14, 202510 min read

Kubernetes Cost Optimization: A Practical Guide

Reduce your Kubernetes spending by 40% or more with these proven strategies. Covers right-sizing, spot instances, autoscaling, and resource quotas.

Kubernetes Cost Optimization: A Practical Guide

The Hidden Cost of Kubernetes

Kubernetes makes deployment easy, but that ease often leads to over-provisioning. We have seen companies waste 40-60% of their cloud spend on unused resources.

Start With Visibility

You cannot optimize what you cannot measure:

Install Resource Monitoring

apiVersion: v1
kind: Pod
metadata:
name: resource-monitor
spec:
containers:
  • name: app
  • resources: requests: memory: "256Mi" cpu: "250m" limits: memory: "512Mi" cpu: "500m"

    Key Metrics to Track

  • CPU utilization vs requests
  • Memory utilization vs requests
  • Pod restart frequency
  • Node utilization
  • Right-Sizing Strategies

    1. Use Vertical Pod Autoscaler (VPA)

    VPA automatically adjusts resource requests:

    apiVersion: autoscaling.k8s.io/v1
    kind: VerticalPodAutoscaler
    metadata:
    name: my-app-vpa
    spec:
    targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-app
    updatePolicy:
    updateMode: "Auto"

    2. Implement Request Quotas

    Prevent teams from over-requesting:

    apiVersion: v1
    kind: ResourceQuota
    metadata:
    name: team-quota
    spec:
    hard:
    requests.cpu: "10"
    requests.memory: "20Gi"
    limits.cpu: "20"
    limits.memory: "40Gi"

    Spot Instances for Non-Critical Workloads

    Save 60-90% on compute:

    apiVersion: v1
    kind: Pod
    metadata:
    name: batch-job
    spec:
    nodeSelector:
    cloud.google.com/gke-spot: "true"
    tolerations:
    
  • key: cloud.google.com/gke-spot
  • operator: Equal value: "true" effect: NoSchedule

    Cluster Autoscaler Configuration

    Scale nodes based on actual demand:

    apiVersion: v1
    kind: ConfigMap
    metadata:
    name: cluster-autoscaler-config
    data:
    scale-down-delay-after-add: "10m"
    scale-down-unneeded-time: "10m"
    scale-down-utilization-threshold: "0.5"

    Quick Wins Checklist

  • Set resource requests and limits on all pods
  • Enable cluster autoscaler
  • Use spot/preemptible instances for batch jobs
  • Implement namespace quotas
  • Review and right-size monthly
  • Conclusion

    Cost optimization is an ongoing process. Start with visibility, implement autoscaling, and review regularly. Small improvements compound into significant savings.

    Related Articles