Kubernetes has always been sensitive to bad inputs. What’s changed is how often teams are running into it. As more bursty workloads—especially inference—land on Kubernetes, a familiar pattern shows up more often: clusters add nodes even when utilization looks fine. The CNCF’s latest annual survey frames Kubernetes as the default platform for running AI in production, which means more teams are now feeling the edges of scheduling and autoscaling behavior that used to stay in the background.
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