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.

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


