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GKE interview questions and answers

Advanced Scenario-Based GKE Interview Questions and Answers (2026)

Advanced Scenario-Based GKE Interview Questions and Answers (2026)


Introduction

Modern enterprises rely on GKE for mission-critical workloads. Interviewers increasingly test real-time troubleshooting, architecture decisions, security hardening, and cost optimization scenarios.

This article covers 20+ advanced, scenario-based GKE interview questions with detailed solutions, designed for 5–10+ years experience professionals.


1. Scenario: Pods Are Pending Even Though Nodes Have Free CPU

Problem:
Pods remain in Pending state, but nodes show available CPU.

Root Cause & Solution:

  • Check memory requests
  • Verify node selectors / affinity
  • Inspect taints and tolerations
  • Check PodDisruptionBudgets

Commands:

kubectl describe pod <pod-name>
kubectl describe node <node-name>

2. Scenario: Sudden Traffic Spike Crashes Your Application

Solution Strategy:

  • Enable HPA (Horizontal Pod Autoscaler)
  • Configure Cluster Autoscaler
  • Use GKE Ingress with Cloud Load Balancer
  • Apply requests/limits

3. Scenario: Node Goes Down and Pods Don’t Restart

Root Cause:

  • Autorepair disabled
  • Single-zone cluster

Fix:

  • Enable node auto-repair
  • Use regional clusters
  • Use ReplicaSets

4. Scenario: Secure Pod Access to Google Cloud APIs Without Keys

Best Practice:

  • Enable Workload Identity
  • Map Kubernetes Service Account to GCP IAM Service Account

Why?

  • Eliminates long-lived service account keys

5. Scenario: Zero-Downtime Application Deployment

Solution:

  • Use Rolling Updates
  • Configure maxSurge & maxUnavailable
  • Implement Readiness Probes

6. Scenario: High GKE Costs Due to Over-Provisioned Nodes

Optimization Steps:

  • Enable Cluster Autoscaler
  • Use Node Auto-Provisioning
  • Use Autopilot
  • Right-size pod requests

7. Scenario: Need Isolation for Different Teams in One Cluster

Solution:

  • Use Namespaces
  • Apply RBAC
  • Use ResourceQuotas
  • NetworkPolicies

8. Scenario: Pods Can’t Communicate Across Namespaces

Cause:

  • NetworkPolicy restrictions

Fix:

  • Modify NetworkPolicy to allow cross-namespace traffic

9. Scenario: Application Needs Static Public IP

Solution:

  • Use Ingress
  • Reserve a global static IP
  • Attach IP to Ingress

10. Scenario: GKE Upgrade Causes Application Downtime

Prevention:

  • Use PodDisruptionBudgets
  • Use Surge upgrades
  • Test in staging clusters

11. Scenario: Logs Missing From Pods

Troubleshooting:

  • Verify Cloud Logging enabled
  • Check container logs to stdout/stderr
  • Validate logging agent status

12. Scenario: Stateful Application Loses Data After Pod Restart

Solution:

  • Use PersistentVolumeClaims
  • Use StatefulSets
  • Use Regional Persistent Disks

13. Scenario: External Users Can’t Access Service

Check:

  • Service type (LoadBalancer)
  • Firewall rules
  • Ingress backend health
  • SSL certificates

14. Scenario: Pod Needs GPU for ML Workloads

Steps:

  • Create GPU-enabled node pool
  • Apply nodeSelector
  • Install NVIDIA drivers (auto in GKE)

15. Scenario: Prevent Unauthorized Image Deployments

Security Controls:

  • Enable Binary Authorization
  • Use Artifact Registry
  • Enforce signed images

16. Scenario: Need Canary Deployment in GKE

Implementation:

  • Use Istio / Service Mesh
  • Use multiple Deployments
  • Traffic splitting via Ingress

17. Scenario: Multi-Region Disaster Recovery Strategy

Solution:

  • Use multiple GKE clusters
  • Use GKE Fleet / Anthos
  • Global Load Balancer
  • Backup using Velero

18. Scenario: Internal Service Must Not Be Exposed Publicly

Fix:

  • Use ClusterIP
  • Internal Load Balancer
  • Private GKE cluster

19. Scenario: CI/CD Pipeline Deploys Broken Code

Prevention:

  • Use Blue-Green deployments
  • Automated tests
  • Rollback strategy using Helm

20. Scenario: Need to Control API Access at Pod Level

Solution:

  • Use RBAC
  • Kubernetes Service Accounts
  • Workload Identity

21. Scenario: Pods Evicted Frequently

Cause:

  • Memory pressure
  • No resource limits

Fix:

  • Set proper resource requests & limits
  • Use Vertical Pod Autoscaler (VPA)

22. Scenario: GKE Cluster Must Meet Compliance Standards

Best Practices:

  • Private clusters
  • Shielded nodes
  • CIS benchmarks
  • Audit logs enabled

23. Scenario: Sudden DNS Resolution Failures

Fix:

  • Enable NodeLocal DNS Cache
  • Check CoreDNS pods
  • Validate DNS policies

24. Scenario: Multi-Tenant GKE Cluster Security

Controls:

  • Pod Security Standards
  • Namespace isolation
  • Network policies
  • Separate node pools

25. Scenario: GKE API Server Access Restricted

Solution:

  • Enable Authorized Networks
  • Use private endpoint
  • Use Bastion host

Conclusion

These advanced scenario-based GKE interview questions reflect real production challenges faced by DevOps and SRE professionals in 2026.

Mastering these scenarios will help you:
✔ Crack senior-level interviews
✔ Design resilient architectures
✔ Troubleshoot faster in production

For more GKE, Kubernetes, DevOps, and Cloud interview guides, visit
👉 www.cloudsoftsol.com

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