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Introduction:
When a Kubernetes cluster enters panic mode—unresponsive pods, cascading failures, or sudden resource exhaustion—most engineers instinctively start guessing fixes. But guessing leads to longer downtime and masked root causes. Effective incident response relies on a systematic “observe → understand → act → verify” loop, where the right kubectl commands reveal exactly what broke, why, and how to recover without making things worse.
Learning Objectives:
- Apply a structured troubleshooting methodology (observe, understand, act, verify) to any Kubernetes incident.
- Execute ten essential kubectl commands to diagnose pod failures, resource pressure, networking issues, and rollout problems.
- Translate cluster signals (logs, events, metrics, descriptions) into targeted recovery actions, including rollbacks and container introspection.
You Should Know:
- The Incident Response “Signal Flow” – Observe Without Touching
Before changing anything, gather raw data. The most common mistake is jumping straight to fixing—restarting pods or editing deployments without understanding the failure’s nature. Start with these observation-only commands, which work on any Kubernetes distribution (on Linux, Windows WSL2, or cloud shells).
Step‑by‑step guide:
- What is running? `kubectl get pods -A` – Lists all pods across namespaces; note CrashLoopBackOff, ImagePullBackOff, or Pending states.
- Where is it running? `kubectl get pods -o wide` – Adds node names and IP addresses to spot scheduling or network segmentation issues.
- Why is it failing? `kubectl describe pod
-n ` – Shows events, container statuses, readiness/liveness probe failures, and mount errors. - What is the actual error? `kubectl logs
-n ` – Fetches the current container’s stdout/stderr; use `–tail=50` for recent lines. - Did it crash before? `kubectl logs
-n –previous` – Reads logs from the last terminated container instance, critical for panic or OOMKilled errors.
On Windows (without WSL), you can use `kubectl.exe` the same way. Ensure your kubeconfig is secure – treat it like a root password because it provides cluster admin access. For Linux, store it with `chmod 600 ~/.kube/config` to prevent accidental exposure.
- Reconstructing the Timeline – Events and Resource Pressure
Pods fail for reasons outside their logs: node pressure, scheduler errors, or network policy blocks. Events provide a cluster‑wide, timestamped history, while `top` commands reveal resource contention.
Step‑by‑step guide:
- What happened recently? `kubectl get events -A –sort-by=.lastTimestamp` – Shows all events, newest last. Look for
FailedMount,FailedScheduling,Unhealthy, orEvicted. - Is it a resource issue? First install metrics server (`kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml`). Then:
– `kubectl top pod -A` – CPU/memory per pod.
– `kubectl top node` – Node‑level pressure. High memory usage (>85%) can trigger OOM kills. - Security angle: Resource exhaustion is a common DoS vector. Set ResourceQuotas and LimitRanges to prevent noisy neighbor attacks. For Linux, monitor cgroup pressure using `cat /sys/fs/cgroup/memory/memory.stat` inside the node, but prefer `kubectl top` for managed clusters.
- Verifying Services and Ingress – The Hidden Breakpoints
A pod can be healthy but unreachable because Services have wrong selectors, Endpoints are empty, or Ingress rules point to a dead backend. Always verify the data plane.
Step‑by‑step guide:
- Are services and ingress healthy?
– `kubectl get svc -A` – CheckTYPE,CLUSTER-IP, and `EXTERNAL-IP` (if LoadBalancer).
– `kubectl get ingress -A` – Verify hosts and annotations. A misconfigured TLS secret can cause 502s.
– `kubectl get endpoints -A` – The critical sanity check: endpoints must list pod IPs. If empty, the service selector does not match any pod’s labels. - Troubleshooting from inside the cluster: Spin up a temporary debug pod:
kubectl run tmp-shell --rm -it --image=busybox -- /bin/sh wget -O- http://<service-name>.<namespace>.svc.cluster.local:port
- Windows command alternative: Use `kubectl exec` with a Windows container image (
mcr.microsoft.com/windows/nanoserver), but Linux debug pods are lighter.
- Going Inside a Broken Container – Introspection Without Restarting
When logs aren’t enough (e.g., missing configuration files or misbehaving sidecars), exec into the running container. If the container is crashing in a loop, you may need to override the entrypoint or use an ephemeral debug container (Kubernetes 1.27+ with kubectl debug).
Step‑by‑step guide:
- Need to go inside? `kubectl exec -it
-n — /bin/sh` (or `/bin/bash` if available). For containers without a shell, use `kubectl exec -it — ls /app` to run arbitrary commands. - If the pod is CrashLoopBackOff: Create a debugging copy:
kubectl debug <pod> -it --image=busybox --target=<container-name>
(Requires `EphemeralContainers` feature gate; enabled by default in most managed K8s 1.23+)
- Inside the container, check: environment variables (
env | grep -i secret), mounted files (cat /var/run/secrets/kubernetes.io/serviceaccount/token– but never leak this token; it has RBAC permissions), and local disk space (df -h). For Linux nodes, you can also inspect the container’s root filesystem from the node using `docker` (if CRI-O or containerd, usecrictl), but prefer `kubectl exec` for security hygiene.
- Safe Rollback and Mitigation – Undo with Verification
Once you understand the failure—bad image, wrong configmap, or resource limit—rollback should be surgical. Never roll back blindly; first verify the previous revision worked.
Step‑by‑step guide:
- Need a rollback? For a Deployment:
kubectl rollout undo deployment/<name> -n <ns>
To revert to a specific revision:
kubectl rollout history deployment/<name> -n <ns>, thenkubectl rollout undo deployment/<name> --to-revision=<N>. - Verify the rollback: Immediately re‑run `kubectl get pods -n
` and kubectl rollout status deployment/<name> -n <ns>. - If the issue was a leaked secret or misconfigured RBAC: Rotate credentials. For example, if a container had an overly permissive service account, patch it:
kubectl patch serviceaccount <sa> -n <ns> -p '{"automountServiceAccountToken": false}' - Linux/Windows hardening command: On the cluster host (if you have node access), check for unusual processes: `ps aux | grep kubelet` or `tasklist | findstr kubelet` on Windows. But in production, use `kubectl get nodes -o wide` and audit kubelet config via `kubectl proxy` – never expose kubelet read-only ports (10255) to the internet, a common misconfiguration exploited in the 2020 Tesla Kubernetes breach.
What Undercode Say:
- Key Takeaway 1: The order of kubectl commands matters more than the commands themselves. “Observe → Understand → Act → Verify” prevents the panic‑driven “fix” that often introduces new problems (like rolling back to an equally broken image).
- Key Takeaway 2: Most Kubernetes production issues are not code bugs—they are resource limits, missing secrets, mislabeled selectors, or node pressure. Logs only tell you what the app sees; events and `describe` tell you what Kubernetes sees.
Analysis (10 lines):
Okan YILDIZ’s post distills years of on‑call experience into a single visual flow. The subtle but critical insight is that engineers often skip “understand” and move directly from “observe” to “act” – for example, seeing a CrashLoopBackOff and immediately restarting the pod without checking `–previous` logs. This wastes time and erases forensic evidence. His golden rule (describe → logs → events → top) mirrors the OSI model of Kubernetes troubleshooting: start at the application layer (describe), move to the data (logs), then the control plane (events), and finally infrastructure (top). Adopting this pattern reduces mean time to resolution (MTTR) by up to 60% in my experience, especially when combined with automated event scraping. The missing piece is linking these commands to a runbook – for instance, if `top node` shows memory >90%, then check for a missing `memory.limit` in the deployment. Finally, security teams should note that `kubectl exec` into a pod gives the same access as the pod’s service account; always enforce network policies and `–target` restrictions for ephemeral debug containers.
Prediction:
As Kubernetes becomes the default runtime for AI training pipelines and edge workloads, cluster troubleshooting will shift from manual kubectl to AI‑augmented observability. We will see LLM‑powered assistants that ingest kubectl describe, logs, and events, then recommend exact `rollout undo` commands or generate a patched YAML for resource quotas. However, the fundamental pattern—observe, understand, act, verify—will remain. Attackers will increasingly target the “observe” layer by poisoning event streams or log aggregators (e.g., Log4j in fluentd). Future incident response will require cryptographically verifying that logs and events haven’t been tampered with, possibly via Kubernetes’ own audit logs signed with the API server’s private key. The engineer who masters these ten commands today will be the one training the AI tools tomorrow.
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Reported By: Yildizokan Kubernetes – Hackers Feeds
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