Troubleshooting complex issues in a Kubernetes environment is a key responsibility for DevOps engineers and site reliability engineers (SREs). Here’s a real-world scenario where diagnosing and resolving an issue required a structured approach and deep understanding of Kubernetes internals.
Scenario Overview
You're managing a Kubernetes cluster hosting a mission-critical microservices application. Users suddenly begin reporting intermittent errors while accessing certain features. Upon inspection, you observe that pods belonging to one specific deployment are restarting frequently, causing service disruptions and degraded performance.
Step-by-Step Troubleshooting Process
1. Check Cluster Health
Start by inspecting the health of the cluster:
bash
kubectl get nodes
kubectl get pods
kubectl describe pod <pod-name>
You verify that the nodes are in Ready state and look for any events indicating resource pressure, disk issues, or node taints affecting pod scheduling.
2. Review Pod Logs
Examine the logs of the crashing or restarting pods:
bash
kubectl logs <pod-name>
Look for exceptions, stack traces, or application-level errors such as failed DB connections, misconfigurations, or timeouts.
3. Analyze Resource Utilization
Utilize monitoring tools like Prometheus, Grafana, or Metrics Server to check:
- CPU and memory usage
- Pod eviction events
- OOMKilled status or crash loops
- These metrics help determine whether the pods are under-provisioned or hitting resource limits.
4. Inspect Network and Service Connectivity
Investigate whether services are communicating properly:
- Run
kubectl exec into running pods and test DNS resolution with nslookup. - Confirm that network policies aren’t inadvertently blocking traffic.
- Validate service selectors and endpoints.
5. Review Configuration Files
Check YAML manifests for:
- Incorrect environment variables
- Bad image versions
- Improper liveness/readiness probe configurations
- Sometimes even a small typo or misconfiguration can trigger pod instability.
6. Scale the Deployment Temporarily
To maintain availability, scale the deployment:
bash
kubectl scale deployment <deployment-name> --replicas=6
This distributes the load and provides redundancy while the investigation continues.
7. Collaborate and Escalate
If the issue persists, loop in senior engineers, SREs, or application developers. You may also reach out to the Kubernetes community on Slack, Stack Overflow, or GitHub Discussions for external insight.
8. Implement Fixes and Monitor the System
After identifying the root cause—whether it's a memory leak, bad config, or code bug—you:
- Adjust resource requests/limits
- Patch or redeploy the app
- Monitor using dashboards to validate stability
9. Document and Share Learnings
Finally, document the incident:
- Timeline of events
- Steps taken and tools used
- Final root cause and fix
- Prevention strategies
- Sharing these insights helps your team learn and prepares you for faster troubleshooting in future incidents.
Conclusion
Kubernetes environments are powerful but can be intricate to troubleshoot. By following a systematic approach—from checking logs and metrics to reviewing configurations and collaborating—you can effectively resolve even the most elusive issues and keep your systems running smoothly.