Most teams accept their Kubernetes bills as "the cost of doing cloud." But in reality, 40-60% of typical K8s spend is waste: over-provisioned nodes, idle resources, inefficient autoscaling, and expensive storage classes. Here's how we consistently cut costs in half without performance trade-offs.

1) Right-size your nodes (start here)

Most clusters run on oversized instances "just to be safe." Use actual resource metrics to pick the optimal instance types.

✓Analyze actual CPU/memory usage over 2 weeks (not requests/limits).
✓Switch to ARM-based instances (Graviton on AWS) for 20-40% savings.
✓Use burstable instances (T-series) for low-traffic workloads.

2) Embrace spot instances for stateless workloads

Spot instances cost 60-90% less than on-demand. With proper pod disruption budgets and node diversity, they're production-ready.

✓Use spot for batch jobs, CI/CD workers, and stateless services.
✓Mix spot with on-demand using node affinity/taints.
✓Set up Karpenter or Cluster Autoscaler spot support.

3) Fix autoscaling before it drains your budget

✓Set HPA based on actual traffic patterns, not guesses.
✓Enable Cluster Autoscaler with proper node group configs.
✓Use scale-down delays to prevent thrashing.
✓Monitor scale-up/down events and tune thresholds.

4) Storage optimization (often overlooked)

✓Don't use premium SSD for logs or temp data (use gp2/standard).
✓Set retention policies on PVCs and delete orphaned volumes.
✓Use volume snapshots strategically, not continuously.

5) Resource requests/limits: the hidden cost multiplier

Overly generous requests waste money; missing limits cause noisy neighbors. Get this balance right.

✓Use VPA (Vertical Pod Autoscaler) recommendations.
✓Set requests = actual usage, limits = 1.5-2x requests.
✓Monitor throttling and OOM kills to tune limits.

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How We Cut Kubernetes Costs by 50% Without Touching Application Code