kubernetes

An experience probe with a depth gauge: 'we used Kubernetes' fails, and so does reciting the KServe README. The stack-process-role-warstory structure, the resource and probe details that prove hands-on work, and where KServe earns its complexity.

CPU-based HPA on GPU inference never fires, the trap half of all candidates fall into within a minute. The signals that actually track load, the anatomy of a five-minute cold start, and which mitigations are worth their cost at each layer.

The cluster shows eight free GPUs and your four-GPU pod still won't schedule, the fragmentation puzzle GPU-platform rounds open with. Bin-packing vs. spreading, MIG/MPS/time-slicing for the small-model problem, and the pod-per-model math that breaks at scale.

A reported OpenAI design prompt. The skeleton: gang scheduling, topology-aware placement, preemption with checkpoint contracts, and quota, plus the fragmentation problem that quietly eats 20% of naive clusters.