Your K8s Cluster Wastes 50-70%
of What You Pay For
Professional Kubernetes cost optimization for EKS, GKE, and AKS. Rightsizing, Karpenter tuning, Spot instances, and GPU optimization. We cut K8s costs 40-60% without risking stability.
6 Kubernetes Cost Optimization Strategies We Implement
Resource Request Rightsizing
Analyze actual CPU/memory usage vs requests. Right-size pods to actual requirements. Stop over-provisioning that forces autoscaler to add unnecessary nodes.
Karpenter / Autoscaler Tuning
Deploy Karpenter for right-sized node provisioning. Enable node consolidation. Diversify instance types for better Spot availability. Replace bloated node groups.
Spot Instance Adoption
Move stateless workloads to Spot/preemptible nodes. Configure disruption budgets and fallback strategies. Diversify across instance types for availability.
GPU Workload Optimization
Scale GPU nodes to zero when idle. Right-size GPU instance types. Use Spot GPUs for training with checkpointing. Separate inference and training pools.
Namespace & Resource Governance
Set resource quotas per namespace. Implement LimitRanges to prevent over-provisioning. Clean up orphaned PVCs and abandoned workloads.
Cost Visibility & Attribution
Deploy Kubecost or OpenCost. Tag workloads to teams and products. Build dashboards that show per-namespace, per-team, per-deployment costs in real time.
Signs Your K8s Cluster Needs Optimization
Stop Overpaying for Kubernetes
Get a free assessment of your K8s cluster costs. We'll show you exactly where compute is being wasted and how much you can save.
Free K8s Cost Assessment