best practices in kubernetes

Here’s a 50-point crisp checklist of Kubernetes production support best practices you can use in interviews — short, sharp, and easy to remember.

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Kubernetes Production Support – 50 Best Practices

A. Cluster & Node Management

1. Keep Kubernetes version up to date with LTS and security patches.
2. Use multiple master nodes for HA (High Availability).
3. Label and taint nodes for workload segregation.
4. Use autoscaling for nodes (Cluster Autoscaler).
5. Reserve system resources on nodes using --system-reserved.
6. Regularly monitor node health via kubectl get nodes.
7. Spread workloads across zones/regions for resilience.
8. Avoid overcommitting node resources beyond safe limits.
9. Ensure OS and kernel are tuned for container workloads.
10. Apply OS-level security updates on nodes regularly.

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B. Pod & Workload Management

11. Use resource requests and limits for all pods.
12. Configure PodDisruptionBudgets to avoid downtime during maintenance.
13. Use Readiness and Liveness probes for health checks.
14. Implement pod anti-affinity to avoid co-locating critical workloads.
15. Use init containers for dependency checks before main app starts.
16. Deploy workloads via Deployment, StatefulSet, or DaemonSet as per use case.
17. Keep images lightweight and scan for vulnerabilities.
18. Avoid running pods as root.
19. Use imagePullPolicy=IfNotPresent for stable deployments.
20. Tag images with version, not latest.

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C. Networking & Service Management

21. Use ClusterIP for internal services, LoadBalancer/Ingress for external.
22. Secure Ingress with TLS (Let’s Encrypt or custom certs).
23. Use NetworkPolicies to control pod-to-pod communication.
24. Avoid exposing the API server publicly.
25. Keep DNS resolution stable via CoreDNS monitoring.
26. Use headless services for Stateful workloads.
27. Implement connection timeouts and retries in services.
28. Configure externalTrafficPolicy=Local for preserving client IP.
29. Limit public access to services via firewalls or security groups.
30. Load-test services before going live.

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D. Observability & Troubleshooting

31. Integrate Prometheus & Grafana for metrics monitoring.
32. Centralize logs via ELK or Loki.
33. Enable Kubernetes audit logging for API server.
34. Set up alerts for pod restarts, CPU/memory saturation.
35. Use kubectl describe and kubectl logs for quick debugging.
36. Maintain runbooks for common incident scenarios.
37. Use kubectl top to identify resource bottlenecks.
38. Set up traceability with OpenTelemetry/Jaeger.
39. Store historical metrics for capacity planning.
40. Regularly test disaster recovery (DR) playbooks.

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E. Security & Compliance

41. Enable Role-Based Access Control (RBAC).
42. Use namespaces for workload isolation.
43. Scan container images before deployment.
44. Use secrets in Kubernetes Secret objects, not plain env variables.
45. Rotate secrets and credentials periodically.
46. Enable API authentication and authorization.
47. Restrict kubectl exec access in production.
48. Use CIS Kubernetes Benchmark for compliance checks.
49. Enable admission controllers (PodSecurity, ValidatingWebhook).
50. Perform periodic security audits with tools like Kube-bench/Kubescape.

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If you want, I can also convert these 50 points into an interview-ready “cheatsheet” in .docx format so you can print and revise quickly.

Do you want me to prepare that formatted docx for you now?