hpa

Turns the standard autoscaling definition into the problem it actually causes. Almost every candidate can define an HPA; far fewer can say why theirs did not save them.

A specific configuration trap with a clean explanation. Both controllers act on the same signal from opposite directions, which can produce unstable feedback depending on their policies and workload.

Utilization-based scaling is the wrong sensor when work arrives as backlog. The design questions are threshold math against drain rate, reaction-time bounds from polling, and why lag-driven fleets oscillate without generous targets and idempotent consumers.

Kubelet resource metrics to metrics-server to aggregated API to HPA controller: every hop adds lag and averaging. Walking the path and naming where it distorts demand separates operators from dashboard readers.

Two controllers with different opinions and no shared hysteresis. Flat traffic with an oscillating node count means the loop is driven by something other than demand, and the candidates are few.