Kubernetes workloads

Kubernetes workloads

The scheduler and the kubelet only know what you declare. Most production pain (evictions, OOMKills, dropped requests during deploys) is a missing or dishonest declaration.

Method

1. Pick the controller for the lifecycle. Deployment for stateless services; StatefulSet only for stable identity/storage (databases, ordered clusters); DaemonSet for per-node agents; Job/CronJob for run-to-completion (with backoffLimit, activeDeadlineSeconds, and idempotent work; see background-jobs). Wrong controller choices surface as workarounds everywhere else.
2. Set requests from measurement; cap memory, not CPU. Requests are the scheduling contract: set them at observed p95 (see get-available-resources thinking: measure, then declare). Memory limit = request (Guaranteed-ish, avoids surprise OOM from overcommit); CPU limit usually omitted, since throttling a bursty service hurts more than sharing. OOMKilled pods mean the limit lies or the app leaks (see memory-leaks).
3. Wire all three probes honestly. Liveness = process health only; readiness = can serve (dependencies); startup covers slow boots so liveness can stay tight; full reasoning in health-checks. Probe mistakes convert dependency blips into restart storms.
4. Make deploys and evictions dropless. preStop sleep a few seconds + SIGTERM handling (see graceful-shutdown), terminationGracePeriodSeconds above request timeout; PodDisruptionBudget (maxUnavailable: 1 or a floor) so node drains and cluster upgrades cannot take the whole service; spread across zones with topologySpreadConstraints, and 2+ replicas or the PDB is fiction.
5. Autoscale on the right signal. HPA on CPU works for CPU-bound services; queue-driven workers scale on queue depth/age (external metrics, KEDA-style); latency-critical paths scale on concurrency or RPS. Set sensible min (cold-start floor) and max (protects downstream; see backpressure), and never HPA+VPA on the same metric.
6. Declare the security posture per pod. runAsNonRoot, readOnlyRootFilesystem, drop all capabilities, no default ServiceAccount token unless the pod calls the API; resource-scoped RBAC when it does (container hardening detail in container-security).
7. Config and secrets flow in declaratively. ConfigMaps/Secrets mounted or injected, rotated by rollout (checksum annotations trigger it); no config fetched at boot from wikis or hand-edited in place (see config-management).

Boundaries

• This covers workload manifests; cluster architecture (node pools, CNI, ingress controllers, upgrade cadence) is platform work with its own review.
• If every service copies the same 200 lines of YAML, the fix is a shared chart/kustomize base owned by platform, not more copying.
• Local dev parity via mini-clusters has limits; test the manifests in a real staging cluster before trusting probes and budgets.