Struggling with Kubernetes at Work? Here is What to Do

Kubernetes is the technology that causes more job stress for DevOps and cloud engineers than almost anything else. It is powerful, complex, and the gap between understanding it conceptually and managing it in production is enormous. If you are struggling with Kubernetes at work right now, this guide is for you.

Why Kubernetes is So Hard in Practice

The theory of Kubernetes — pods, deployments, services — is learnable. The practice is where engineers struggle. Production Kubernetes clusters are complex systems with dozens of interacting components. When something breaks, it can be almost impossible to diagnose alone, especially if you are new to the cluster.

The most common reasons engineers struggle include: limited exposure to network policies and ingress configuration, unfamiliarity with RBAC and security policies, not knowing how to read and interpret Kubernetes events and logs effectively, and never having set up or managed persistent storage in production.

The 10 Most Common Kubernetes Blockers at Work

• Pod CrashLoopBackOff — the pod keeps restarting. Usually a configuration error, missing environment variable or resource limit too low.
• ImagePullBackOff — Kubernetes cannot pull the Docker image. Usually an authentication issue with the container registry.
• Pending pods — pods are not being scheduled. Usually insufficient cluster resources or node selector issues.
• Service not reachable — your service is running but nothing can connect to it. Usually a label selector mismatch or wrong port configuration.
• Ingress not routing traffic — the ingress is configured but traffic is not reaching the pods. Usually an annotation or path configuration issue.
• PersistentVolume not binding — the PVC is stuck in Pending. Usually a StorageClass mismatch or capacity issue.
• Helm deployment failing — the Helm chart is failing to install or upgrade. Usually a values file error or pre-existing release conflict.
• HorizontalPodAutoscaler not scaling — the HPA is defined but not triggering. Usually missing metrics-server or incorrect resource requests.
• RBAC permission denied — your application cannot access the Kubernetes API. Missing ClusterRole or RoleBinding.
• OOMKilled — the container is being killed due to memory. Resource limits set too low or a genuine memory leak.

A Debugging Framework That Actually Works

When something breaks in Kubernetes, follow this sequence:

1. Run kubectl get pods -n [namespace] — identify the problematic pod and its status
2. Run kubectl describe pod [pod-name] -n [namespace] — read the Events section at the bottom carefully
3. Run kubectl logs [pod-name] -n [namespace] --previous — check logs from the previous container run
4. Check resource utilisation with kubectl top pods and kubectl top nodes
5. Check network connectivity with a temporary debug pod

Eighty percent of Kubernetes problems are diagnosed within the first three steps.

When You Need Expert Help

Some Kubernetes problems are genuinely difficult — complex networking issues, cluster-level misconfigurations, multi-team permission structures. If you have been stuck on something for more than a few hours and it is impacting your work, getting an expert DevOps developer to join your screen can resolve in 30 minutes what might take you two days to figure out alone.

Our DevOps developers at Samyak Job Support have managed enterprise Kubernetes clusters at scale and have seen virtually every production failure pattern. A session is often not just about fixing the immediate problem — it is about understanding why it happened so you can prevent it in future.

← Back to all articles