Ingress and Gateway Boundaries

Everything covered so far - Services, EndpointSlices, DNS - operates below the HTTP layer; they route by IP and port, with no concept of a URL path or hostname. To route real web traffic like shop.example.com/checkout to the right backend Service, you need an Ingress object (or the newer Gateway API), which describes host- and path-based routing rules in front of one or more Services. Here is the detail that trips up almost every newcomer: creating an Ingress object by itself does absolutely nothing on its own - it is inert data sitting in etcd until a compatible ingress controller (a real running piece of software, such as Kong, NGINX Ingress or Traefik) is deployed, watches for Ingress objects, and actually implements the routing rules described in them. Once a controller is in place, the full request path involves several more moving parts working together: TLS termination (where HTTPS decryption happens), path rewriting, the controller's own health checks toward backend Pods, whether the original client's IP address is preserved through the hop or replaced, and a long list of controller-specific annotations that configure behavior the base Ingress spec does not cover.

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 request to Kong returns HTTP 503 ("Service Unavailable") even though the Ingress rule, read on its own, looks completely correct. Rather than randomly trying different annotations, trace the request the same way it actually travels: does the gateway's route match the correct backend Service and port? Does that Service have any ready endpoints in its EndpointSlice? Is there a NetworkPolicy silently blocking the gateway's own traffic to those Pods? Each hop in that chain can independently produce a 503, and only tracing the chain in order reliably finds which one actually failed.

Trace ingress as a chain

Verify the controller accepted the Ingress or HTTPRoute, its address is reachable, host and path match, backend Service port resolves, EndpointSlices contain ready Pods, and policy allows the controller namespace. Test with the correct Host header: curl -H 'Host: shop.example.com' http://GATEWAY/path. Then inspect controller logs and generated configuration rather than guessing annotations.

Scenario: The gateway returns 404, which means the request reached a gateway but matched no route; a 503 usually means a route matched but has no usable backend. Controller-specific responses refine the next hop.
Warning: TLS success at the gateway says nothing about encryption from gateway to backend. Decide termination and re-encryption boundaries explicitly, including certificate ownership and rotation.

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 networkpolicy-kong-routing. Open /labs/kubernetes, choose networkpolicy-kong-routing, 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.