Kubernetes cost optimization fails without visibility and shared ownership. Learn how to expose cost per service, avoid chargeback pitfalls, and align engineering teams with efficient resource usage—without creating friction. Before We Talk About Cost, Let’s Talk About Everything We’ve Ignored So Far By now, the technical picture is clear. We’ve seen how clusters waste capacity because requests are inflated. We’ve unpacked how requests and limits shape scheduling in ways most teams underestimate. We’ve looked at autoscaling and how it quietly depends on honest inputs. And we’ve gone deep into GPU workloads, where inefficiency turns into direct financial loss. At this point, you might expect cost optimization to be straightforward. Fix requests, tune autoscaling, redesign GPU scheduling — problem solved. But that’s not how it plays out in real organizations. Because even after you fix the technical side, one problem remains: Nobody feels responsible for the cost.…