Kubernetes Cost Optimization: A Practical Guide
Learn proven strategies to reduce your Kubernetes spending by up to 60% without compromising reliability or performance.
Kubernetes is powerful, but it’s easy to overspend. Many organizations run clusters at 15-25% utilization while paying for 100% of provisioned capacity. Here’s how to fix that.
Common Sources of Waste
The biggest culprits are over-provisioned resource requests, idle namespaces, and lack of autoscaling. Most teams set generous CPU and memory requests “just in case” and never revisit them.
Optimization Strategies
- Implement Vertical Pod Autoscaler (VPA) — Let Kubernetes right-size your pods based on actual usage
- Use Horizontal Pod Autoscaler (HPA) — Scale out during peak traffic, scale in during quiet periods
- Leverage spot/preemptible instances — Save 60-90% on non-critical workloads
- Set resource quotas per namespace — Prevent teams from over-provisioning
- Use cluster autoscaler — Match node count to actual demand
Monitoring is Key
You can’t optimize what you don’t measure. Tools like Kubecost, cloud-native monitoring, and custom Prometheus metrics give you the visibility needed to make informed decisions.
Start with the low-hanging fruit — right-sizing resource requests alone can save 30-40% on your Kubernetes bill.
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