DevOps engineering is one of the highest-pressure roles in IT — when a CI/CD pipeline fails or a Kubernetes deployment breaks, every minute of downtime has visibility. This guide covers the most common DevOps production issues and how real-time expert support unblocks them quickly.
Pipeline failures are the most frequent DevOps support request. Common failure patterns include:
Kubernetes is powerful but has a steep operational learning curve. Most deployment issues fall into predictable patterns: pods that never start (image issues, resource limits, config map errors), services that do not route traffic correctly (selector mismatch, ingress misconfiguration), and storage volumes that fail to mount (PVC binding, storage class issues).
Terraform errors in production environments carry real risk. Common issues include state lock conflicts (another process holds the state lock), provider version incompatibilities causing plan failures, dependency cycles in resource graphs, and destroy operations that are broader in scope than intended. Expert review before applying destructive plans is a common support request.
Helm chart debugging requires understanding the template rendering pipeline. Common issues include values file overrides not applying as expected, Helm hook ordering problems, and chart upgrade failures due to immutable field changes. ArgoCD issues often involve sync status stuck in "OutOfSync" despite applying changes, RBAC permission errors, or resource health checks failing.
When a release is failing in production and the team needs to decide between hotfix, rollback, or continued troubleshooting, expert support helps structure that decision quickly. The decision framework: estimate time to fix vs time to rollback, assess blast radius of current failure, evaluate rollback risk (database migrations that cannot be reversed), and communicate a clear timeline to stakeholders.
Docker support covers multi-stage build failures, layer caching problems causing stale builds, container networking issues in docker-compose environments, and production container resource limits causing OOM kills. For microservices, networking between containers — service discovery, DNS resolution, and port mapping — accounts for a large share of support requests.
Docker build failures from base image changes, test flakiness causing pipeline instability, artifact upload timeouts, and environment variable or secret misconfiguration account for the majority of CI/CD failures.
Start with kubectl describe pod to see events. Check the container logs with kubectl logs. Verify that the image is accessible. Check resource requests and limits. Review ConfigMap and Secret mounts.
Identify who holds the lock (DynamoDB lock table for S3 backend). If the locking process has ended, force-unlock with terraform force-unlock [LOCK_ID]. Never force-unlock if another apply is genuinely running.
In ArgoCD, sync status and app health give you the current state. Check application events for the failure reason. Rollback in ArgoCD by reverting the Git commit that triggered the broken state and letting ArgoCD sync to the previous known-good version.
You share the failing pipeline, error logs, and relevant infrastructure configuration. The expert identifies the failure point, explains the root cause, guides the fix, and helps you add a preventive check to avoid recurrence.
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