10/02/2026
☸️ Common Kubernetes Production Issues Every DevOps Engineer Should Know
Deploying an application to Kubernetes is only the beginning. In a real production environment, engineers must know how to identify failures, troubleshoot quickly, find the root cause, and restore services safely.
At NewEra Solutions Academy, we focus on practical, real-world scenarios you are likely to encounter as a DevOps, Cloud, SRE, Platform, or DevSecOps Engineer.
🔎 10 common Kubernetes production issues:
1. 🔄 CrashLoopBackOff — A container repeatedly starts and crashes. Check logs, configuration, environment variables, dependencies, exit codes, and health probes.
2. 📦 ImagePullBackOff — Kubernetes cannot pull the container image. Verify the image/tag, registry permissions, imagePullSecrets, and connectivity.
3. ⏳ Pod Pending — The scheduler cannot place the pod on a node. Check CPU/memory capacity, taints/tolerations, affinity rules, and storage requirements.
4. 🌐 Service Not Accessible — The application is running but traffic cannot reach it. Investigate Service selectors, endpoints, ports, NetworkPolicies, and pod health.
5. 🚨 Ingress 502/503 — The Ingress cannot successfully route traffic to a healthy backend. Check Ingress rules, Service ports, endpoints, readiness probes, controller logs, and timeouts.
6. 💾 OOMKilled — A container exceeds its memory limit and Kubernetes terminates it. Review memory consumption, requests/limits, and possible application memory leaks.
7. 🖥️ Node NotReady — A worker node becomes unhealthy. Investigate kubelet, networking, disk/memory/CPU pressure, container runtime, and node events.
8. 💽 PV/PVC Not Bound — Kubernetes cannot provide the storage requested by the application. Check the StorageClass, capacity, access modes, CSI driver, PV, and PVC events.
9. 🔎 DNS Resolution Failure — Pods cannot resolve Services or external domains. Check CoreDNS, NetworkPolicies, DNS configuration, and cluster networking.
10. 📈 High CPU/Memory Usage — Excessive resource consumption can cause slow applications and instability. Monitor usage, optimize the workload, configure appropriate requests/limits, and use autoscaling where appropriate.
🛠️ Troubleshooting starts with evidence
Before restarting or redeploying, investigate:
kubectl get pods -A
kubectl describe pod -n
kubectl logs -n
kubectl logs -n --previous
kubectl get events -n --sort-by=.metadata.creationTimestamp
kubectl top pods -n
kubectl top nodes
A strong DevOps engineer doesn't just know how to deploy Kubernetes workloads — they understand how the components interact and how to troubleshoot them when production fails.
🎓 Learn Kubernetes, AWS, Linux, Docker, Terraform, CI/CD, Jenkins, GitHub Actions, Monitoring, DevSecOps, and real-world troubleshooting with NewEra Solutions Academy.
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