How to Cut Kubernetes Costs by 30–50% Using Node Right-Sizing

Right-sizing nodes delivers the biggest and fastest savings because you can do it without touching application code. Follow this three-phase plan to safely shrink your AWS bill.

Phase 1: Observe and baseline

1. Collect utilization: Use ClusterCost to aggregate CPU and memory headroom per node group over a rolling 14-day window.
2. Segment workloads: Identify which namespaces need high-memory vs. compute-optimized nodes.
3. Measure disruption tolerance: Check PodDisruptionBudgets and maintenance windows.

Output: a scorecard showing current utilization, idle nodes, and potential savings.

Phase 2: Simulate better configurations

Use the following levers:

• Instance families: Switch from general-purpose (m6i) to workload-specific (c7g for CPU, r7i for memory, g5 for GPU).
• Size mix: Replace many small nodes with fewer large nodes (or vice versa) to reduce overhead.
• Purchase options: Blend 60% reserved, 20% spot, 20% on-demand as a starting point.
• Scheduling enhancements: Introduce Karpenter or Cluster Autoscaler with topology-aware scheduling.

ClusterCost’s planner lets you try scenarios like “What if we move staging to spot-only?” and shows the expected cost delta.

Phase 3: Execute and verify

1. Create new node groups with desired specs.
2. Use taints/affinity to migrate workloads gradually.
3. Drain old nodes using kubectl drain --delete-emptydir-data=false.
4. Track savings via ClusterCost reports week over week.

Expected ROI: teams typically reclaim 30–50% of compute spend within two sprints.

Extra credit: automate continuous right-sizing

• Integrate ClusterCost with GitOps so node group configuration is code-reviewed.
• Trigger simulations automatically when utilization drops below thresholds.
• Pair with pod right-sizing so supply (nodes) and demand (requests) stay aligned.

Right-sizing nodes turns infrastructure from a fixed cost into a flexible lever your platform team can dial up or down in response to business needs.***