DevOps Interview Questions – Industry Standard (25 Q&A)

Designed for L2 / L3 DevOps, SRE, Platform Engineer interviews. Covers architecture, CI/CD design, production failures, LAB commands, and field scenarios.

1️⃣ DevOps Fundamentals & Architecture

DevOps Lifecycle and Toolchain
Q1. Explain DevOps from an enterprise architecture perspective.
  1. DevOps is an operating model, not a toolset.
  2. Git is the single source of truth.
  3. CI/CD automates build, test, deploy.
  4. Infrastructure is managed via IaC.
  5. Monitoring and feedback close the loop.
Q2. Scenario: Deployment is successful but users see 500 errors.
Production deployment is green, but customers report application failures.
  1. Check application logs
  2. Verify config and secrets
  3. Check downstream dependencies
  4. Review monitoring dashboards
  5. Rollback if required
Q3. Explain the CALMS model.
Culture, Automation, Lean, Measurement, Sharing – applied together in real teams.
Q4. How does DevOps reduce MTTR?
Monitoring → Alert → Runbook → Auto-rollback → Postmortem.
Q5. Common DevOps anti-patterns seen in enterprises?
Tool-driven DevOps, siloed teams, manual approvals, no ownership of production.

2️⃣ CI/CD – Design & Troubleshooting

CI/CD Pipeline Architecture
Q6. Design a CI/CD pipeline for microservices.
  1. Code commit to Git
  2. Static analysis (SAST)
  3. Unit & integration tests
  4. Docker image build
  5. Security scan
  6. Deploy to staging
  7. Canary / Blue-Green production deploy
Q7. LAB: Check Jenkins pipeline logs
kubectl logs jenkins-0 -n jenkins
Q8. Scenario: Pipeline passes but production fails.
Build and tests passed, but pods crash after deployment.
  1. Missing secrets
  2. Environment variable mismatch
  3. Incorrect image tag
  4. Resource limits differ from staging
Q9. How do you secure CI/CD pipelines?
Vault-based secrets, RBAC, artifact signing, pipeline isolation.
Q10. What is GitOps and why companies adopt it?
Git defines desired state; systems reconcile actual state automatically.

3️⃣ Docker & Containerization (Production Reality)

Docker Architecture Diagram
Q11. What real problems do containers solve?
Environment drift, dependency conflicts, slow deployments.
Q12. LAB: Debug a crashing container
docker ps -a
docker logs <container_id>
docker exec -it <container_id> /bin/sh
Q13. Scenario: Container works locally but fails in Kubernetes.
ConfigMaps missing, secrets not mounted, wrong resource limits.
Q14. How do you optimize Docker images?
Multi-stage builds, minimal base images, remove build tools.
Q15. Explain Docker networking modes.
Bridge (single host), Overlay (multi-host), Host (high performance).

4️⃣ Kubernetes – Design & Failure Handling

Kubernetes Architecture Overview
Q16. Explain Kubernetes architecture end-to-end.
Control plane (API server, scheduler, controllers) and worker nodes (kubelet, runtime).
Q17. LAB: Troubleshoot a failing pod
kubectl get pods
kubectl describe pod <pod-name>
kubectl logs <pod-name>
Q18. Scenario: Service is running but not reachable.
Check selectors, endpoints, ingress, and network policies.
Q19. How does Kubernetes ensure zero downtime?
Rolling updates, readiness probes, multiple replicas.
Q20. StatefulSet vs Deployment – real use case?
Databases use StatefulSet; stateless apps use Deployment.

5️⃣ Infrastructure as Code & Field Scenarios

Terraform Infrastructure as Code
Q21. Why is IaC mandatory in large enterprises?
Consistency, auditability, faster disaster recovery.
Q22. LAB: Terraform workflow
terraform init
terraform plan
terraform apply
Q23. Scenario: Terraform apply deleted production resources.
Wrong workspace, bad state file, missing lifecycle rules.
Q24. Scenario: Sudden traffic spike brings system down.
Autoscaling, caching, rate limiting, DB tuning.
Q25. How would you design DevOps for telecom-grade systems?
High availability, zero downtime, strong observability, automated recovery.
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