Introduction Running Kubernetes in production is powerful — but the bills can spiral fast. When I first deployed my workloads, my monthly cloud cost felt like a second rent payment. After months of tweaking, I managed to cut my Kubernetes cluster cost by ~60% — without compromising on performance or availability. In this post, I'll walk through the exact techniques that worked for me. 1. Right-Size Your Resource Requests and Limits Most engineers set CPU and memory requests based on guesswork. This leads to over-provisioning — the silent killer of cloud budgets. What I did: Used kubectl top pods and Prometheus metrics for real usage data Reduced over-allocated requests by analyzing 7-day P95 usage Set realistic limits (not 10x the request) Tools that helped: Goldilocks Vertical Pod Autoscaler (VPA) 💡 Lesson: Requests should reflect reality, not paranoia. 2. Use Spot / Preemptible Nodes for Non-Critical Workloads Spot instances can be 70-90% cheaper than on-demand nodes.…