The Kubernetes Network Model

Each Pod receives a routable cluster IP and containers inside it share localhost. Pods can address Pods without NAT in the abstract model; the CNI implementation supplies routes, overlays or eBPF programs. Nodes, Pods, Services and external clients occupy distinct address scopes. Start diagnosis by naming the source and destination scope.

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 Pod can curl another Pod IP on the same node but not across nodes. That points below Services toward CNI routing, encapsulation, firewall or MTU.

Locate the broken hop

Name source Pod, source node, destination type, destination port and protocol. Test DNS, Service IP and direct endpoint separately from a disposable client: kubectl run netcheck --rm -it --image=curlimages/curl -- sh. A direct Pod IP failure suggests CNI routing, firewall or application listen address; Pod IP success plus Service failure points toward selectors, EndpointSlices or the Service dataplane. Cross-node-only failure suggests encapsulation, routes, MTU or host firewall.

Scenario: Small responses succeed but large TLS requests hang across nodes. An overlay MTU mismatch fragments or drops packets. Service YAML changes cannot repair that dataplane symptom.
Warning: Debug Pods must use relevant namespace, labels and ServiceAccount; otherwise policy tests do not reproduce the workload's path.

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 service-dns-networking. Open /labs/kubernetes, choose service-dns-networking, 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.