Scenario-Based Questions you must know as Cloud DevOps Engineer

Hi Inner Circle,

Let’s talk about one of the most high-stakes—and underprepared-for—parts of landing a DevOps role today.
Yes, I’m talking about scenario-based interview questions.

In the world of Cloud DevOps, technical know-how is expected—but what really separates a solid candidate from a standout one is how they solve real-world problems under pressure. And that’s exactly what scenario-based interviews test.

Think about it: You’re asked to fix a broken CI/CD pipeline, debug a Kubernetes CrashLoopBackOff, or respond to a sudden cloud cost spike. These aren't textbook questions. They're drawn straight from the trenches of production systems.

So… what would you choose below?

Why are scenario-based questions so crucial in Cloud DevOps interviews?
Select one from the below (or maybe... all of them 😉):

☑️ They reveal your ability to troubleshoot under pressure.
☑️ They test practical skills—not just theory.
☑️ They reflect the complexity of real production environments.
☑️ They show how well you think, communicate, and prioritize during a crisis.

My goal now is to make you aware of these questions(and potential resolution strategies) so you can tailor your learning accordingly.

I’ll be sharing them in multiple parts—because this list is a long one, my friends.

Let’s dive into Part 1…

1. Diagnosing High Latency in a Cloud-Native Application (Performance)

→ Check Cloud Monitoring dashboard or Grafana metrics
→ Analyze API Gateway or Load Balancer latency
→ Inspect backend service logs and DB query times
Note: Start with metrics, then drill down to logs

2. Troubleshooting Kubernetes Pod Stuck in CrashLoopBackOff State

→ Run kubectl logs <pod> and kubectl describe pod
→ Check for missing env vars, config errors, or failed init containers
→ Validate resource limits and probe configurations
Note: Misconfigurations in startup or probes often cause this

3. Fixing Broken CI/CD Pipeline in DevOps Workflow

→ Examine CI/CD logs (Jenkins/GitHub Actions)
→ Check for syntax errors in pipeline files or invalid paths
→ Validate all environment variables and secret access
Note: Always test stages locally before pushing to main

4. Securing Publicly Exposed Storage Buckets Properly

→ Block all public access via cloud settings (AWS/GCP/Azure)
→ Enforce encryption (SSE-S3/SSE-KMS)
→ Use IAM roles and bucket policies to restrict access
Note: Set up logging (e.g., AWS CloudTrail) to audit access

5. Resolving Terraform Apply Failures in Cloud Infrastructure Provisioning

→ Run terraform validate and plan to identify syntax or resource issues
→ Check for permission or quota errors in cloud provider
→ Use state file locking and inspect dependency order
Note: Split modules and use workspaces for multi-env support

6. Debugging Failed Deployments in Kubernetes Environments

→ Inspect kubectl rollout status and kubectl describe deployment
→ Analyze pod logs for errors (imagePullBackOff, misconfigurations)
→ Validate manifests or Helm chart values
Note: Use kubectl diff or Helm dry-run before apply

7. Investigating Unexpected Cloud Cost Spikes and Budget Overruns

→ Use AWS Cost Explorer, GCP Billing dashboards or Azure’s equivalent billing service (pick OCI dashboard if that’s the cloud provider you’re working on)
→ Identify underutilized instances and unused resources (Volumes, IPs)
→ Set up budgets with alerts and enforce tagging policies
Note: Implement automation to shut down dev/test workloads

8. Handling Issues in Blue-Green Deployment Rollout Failures

→ Check readiness probes and health checks in new version
→ Analyze traffic routing rules and misconfigurations
→ Revert DNS/load balancer switch if necessary
Note: Automate rollback using traffic-weighted tools (e.g., Argo Rollouts)

9. Solving IAM Permission Errors and Access Denied Problems

→ Check error message and resource ARN
→ Validate IAM policy JSON using IAM Policy Simulator
→ Ensure correct role/assume-role is being used
Note: Least privilege principle should be enforced and tested in staging

10. Fixing Service Communication Failures Inside Kubernetes Clusters

→ Check DNS resolution via nslookup inside pods
→ Ensure Services are correctly defined (ClusterIP/Headless)
→ Validate NetworkPolicies or CNI plugin (e.g., Calico) configurations
Note: Use kubectl exec and curl/wget to test inter-service connectivity

🔁 Advanced Level Scenarios

11. Monitoring a Microservices Application (one example)

→ Use Prometheus to scrape metrics and Grafana to visualize (one example)
→ Implement distributed tracing via OpenTelemetry
→ Centralize logs via ELK or Loki stack
Note: Define SLIs per service (latency, availability)

12. Securing Kubernetes Clusters (K8s Security)

→ Enable RBAC, restrict default service accounts
→ Apply NetworkPolicies and PodSecurityStandards
→ Use image scanning tools (Trivy, Clair)
Note: Periodically audit access via kubectl auth can-i

13. Scaling Applications to Handle Sudden Traffic Spikes

→ Use Horizontal Pod Autoscaler and Cluster Autoscaler
→ Enable caching (Redis, CDN like CloudFront)
→ Offload static assets and use load balancing
Note: Set proper resource requests/limits for stability

14. Secure Container Debugging Access (Access Control)

→ Restrict kubectl exec permissions via RBACr
→ Use temporary access tokens or session managers
→ Enable audit logging of all exec actions
Note: Use ephemeral debug containers for sensitive environments

15. Container Won’t Start in Docker/K8s

→ Run docker logs or kubectl logs
→ Validate Dockerfile and CMD/ENTRYPOINT
→ Check image tag, volumes, and permissions
Note: Use docker run locally before K8s deploy

16. Blue-Green vs. Canary Deployment Decision Making

→ Use blue-green for large version jumps or when rollback must be instant
→ Use canary for incremental traffic shifting with metrics validation
→ Automate both with ArgoCD or Flagger
Note: Choose strategy based on risk tolerance

17. Handling K8s deployments for Memory Leak

→ Identify process or pod using kubectl top or Prometheus
→ Restart affected pod or service and check logs
→ Create memory profiling dashboard and alerts
Note: Document RCA and add leak detection in CI

18. Safe Database Migration in Production (DBOps)

→ Backup database before migration
→ Use tools like Flyway, Liquibase with versioning
→ Test rollback scripts in staging
Note: Apply schema changes gradually or via feature toggles

19. Fixing Misconfigured Kubernetes Ingress

→ Validate Ingress manifest for correct host/path rules
→ Confirm backend service and TLS certs
→ Use kubectl describe ingress and NGINX logs for clues
Note: Match annotations with your Ingress controller (NGINX, Traefik)

20. Creating a High Availability Architecture on cloud

→ Use Multi-AZ deployments (compute, databases)
→ Implement Load Balancer + Auto Scaling Groups
→ Add DNS health checks for DNS-based failover
Note: Use Well-Architected Framework as a guide

Certifications and tools matter—but it’s your thinking process that gets you hired.

Even with all the automation and AI in today’s stacks, your ability to solve real problems in real time is still the most valuable skill in DevOps.

Says who?

Yours truly!

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