Pod Security and Supply Chain

Pod Security Admission enforces privileged, baseline or restricted profiles by namespace labels. Image policy adds signature, provenance and vulnerability controls through admission or CI. Pin immutable digests for high-assurance releases and keep registry credentials narrowly scoped.

Analogy: Kubernetes is a thermostat, not a remote control. You declare the temperature; independent controllers measure reality and keep acting. Debugging means finding which sensor, rule or actuator prevents convergence.

Read the object as evidence

kubectl get RESOURCE NAME -n NAMESPACE -o yaml
kubectl describe RESOURCE NAME -n NAMESPACE
kubectl get events -n NAMESPACE --sort-by=.metadata.creationTimestamp
kubectl explain RESOURCE.spec

Do not memorize these as a ritual. The first command exposes desired and observed state, the second connects conditions and events, the third supplies a timeline, and the fourth checks the server's schema. Compare what the controller was asked to do with what it reports doing. Then test the narrowest hypothesis.

Scenario: A signed image still contains a critical vulnerable library. Signing proves origin and integrity, not safety; scanning, patch cadence and runtime hardening remain necessary.

Layer admission and supply-chain controls

Pod Security Admission labels namespaces as privileged, baseline or restricted with enforce, audit and warn modes. Roll out with audit/warn, inventory violations, then enforce at a pinned policy version. Image signatures prove an artifact's identity and provenance; vulnerability scanning assesses known packages; runtime policy constrains behavior. None replaces the others.

Scenario: A trusted signed image is rebuilt from a compromised dependency and passes signature verification. Provenance identifies who built it, while dependency pinning, scanning and response determine whether it is safe to run.
Tip: Pin production images by digest, retain human-readable version annotations, and define emergency policy exceptions with owner, expiry and audit trail. An undocumented bypass becomes permanent policy.

Production reasoning

Ask four questions: Who owns this object? What dependency must become ready next? Which controller reports the blocking condition? What evidence would disprove my current theory? This prevents symptom-driven changes. Record the context, namespace, object generation, image digest and recent rollout before mutation; a recreated Pod may erase the evidence you needed.

Warning: Running is not the same as ready, healthy, durable or correct. Kubernetes status is layered. Confirm the application-level outcome as well as the object state.
Goal: Put this model into practice in the Kubernetes lab restricted-security-context. Open /labs/kubernetes, choose restricted-security-context, predict the failure path before changing anything, then use the simulator's check command to validate the finished state.

Deliberate practice

Before the lab, write the expected object relationship and the first three commands you will run. Afterward, explain why the fix converged and name one tempting change that would only mask the symptom. Repeat using an explicit namespace and a structured output format. This prediction-observation-explanation loop is what turns command familiarity into production judgment.

45-minute investigation

  1. Map (5 min): draw the owner-to-child chain and mark every namespace, selector, identity and dependency involved.
  2. Predict (5 min): write one expected status condition, one likely event and one log or metric signal before opening the lab.
  3. Observe (10 min): collect YAML, describe output and ordered events. Do not mutate state. Record which observation disproves your first theory.
  4. Repair (15 min): make the smallest declarative correction, watch the responsible controller converge, and verify the user-facing path rather than stopping at Running.
  5. Stress (10 min): change one relevant constraint - replica count, label, readiness, resource value or placement rule - predict the outcome, observe it, then restore the known-good declaration.
Tip: Keep a short incident note with symptom, evidence, hypothesis, change, result. Across four sections this produces a reusable runbook instead of a pile of remembered commands.