Kubernetes scheduling often looks effortless in early learning. You deploy a workload, pods appear, and everything seems under control until real production traffic arrives and suddenly the scheduler’s “autopilot” decisions start causing surprises.
In real clusters, nodes are far from identical. Some are lightweight, some are memory-rich, some include
