Kubernetes Workloads

DevOps

Kubernetes workloads, CI/CD pipelines, artifact digests, supply-chain controls, Git rebase, merge, and recovery, and Terraform state, modules, and safe change you can defend in interviews.

• Kubernetes Workloads

  6 studies
  1. 1.Kubernetes Workloads — Deployments, Probes, Resources & Progressive DeliveryControllers reconcile desired vs actual. Deployments own ReplicaSets that own Pods. Probes gate traffic and restarts. Requests/limits set QoS and scheduling. Rollouts need PDBs and a progressive strategy. This hub maps the cluster; Ingress/Gateway stays in the Private Networking pages.
  2. 2.Pods, ReplicaSets & Deployments — Desired State & ControllersThe Deployment controller owns ReplicaSets that own Pods. Labels and selectors wire the tree. maxUnavailable/maxSurge and revision history define how a rollout moves. Prefer Deployments over hand-managing ReplicaSets.
  3. 3.Probes & Pod Lifecycle — Liveness, Readiness, Startup & PreStopStartup probes buy slow boots. Readiness gates Service traffic. Liveness restarts stuck processes — never point it at a dependent database or you restart-storm yourself. PreStop plus terminationGracePeriodSeconds is how you drain cleanly.
  4. 4.Requests, Limits & QoS — CPU Throttling, Memory OOM & SchedulingRequests drive scheduling; limits cap cgroups. Guaranteed / Burstable / BestEffort decide who dies under pressure. CPU over limit throttles; memory over limit OOMs. Overcommit without quotas is how noisy neighbors win.
  5. 5.Rolling, Blue-Green & Canary — Strategies, PDBs & Blast RadiusRollingUpdate trades surge capacity for gradual replacement. Blue-green switches a Service between two Deployments. Canary shifts a fraction of traffic (Flagger/Argo Rollouts). PDBs bound voluntary disruption so you do not drain yourself offline.
  6. 6.HPA, VPA & Autoscaling Gotchas — Metrics, Stabilization & ThrashHPA scales replicas from CPU/memory/custom/external metrics. Stabilization windows stop flap. VPA changes requests/limits and fights HPA if both target the same resource. Queue consumers often need custom metrics, not raw CPU.