Work through a resource request

Set an initial resource profile for a small API that usually uses 120m CPU and 180Mi memory, spikes to 350m and 420Mi during deploy warm-up. Choose Kubernetes CPU and memory requests that reflect observed workload needs. The common shortcut is to paste a template value into every workload. That may either waste cluster capacity or create noisy-neighbor behavior because the scheduler receives bad information. Read observed baseline and spike Baseline: 120m/180Mi. Spike: 350m/420Mi during warm-up. Requests should not be random; they need evidence. Choose request for reliable placement Start near normal plus modest headroom, for example 200m CPU and 256Mi…

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