Google Cloud Professional Cloud DevOps Engineer — Question 193

Your company has an application deployed on Google Kubernetes Engine (GKE) consisting of 12 microservices. Multiple teams are working concurrently on various features across three envi-ronments: Dev, Staging, and Prod. Developers report dependency test failures and delayed re-leases due to deployments from multiple feature branches in the shared Dev GKE cluster.

You need to implement a cost-effective solution for developers to test their microservice features in a stable development environment isolated from other development activities. What should you do?

Answer options

• A. Automate CI pipelines by using Cloud Build for container image creation and Kubernetes manifest updates from main branch merge requests. Integrate with Config Sync to test new im-ages in dynamically created namespaces on the Dev GKE cluster with autoscaling enabled. Im-plement a post-test namespace cleanup routine.
• B. Automate CI pipelines by using Cloud Build to create container images and update Kuber-netes manifests for each commit. Use Cloud Deploy for progressive delivery to Dev, Staging, and Prod GKE clusters. Enable Config Sync for consistent Kubernetes configurations across en-vironments.
• C. Use Cloud Build to automate CI pipelines and update Kubernetes manifest files from feature branch commits. Integrate with Config Sync to test new images in dynamically created namespaces on the Dev GKE cluster with autoscaling enabled. Implement a post-test namespace cleanup routine.
• D. Use Cloud Build to automate CI pipelines and update Kubernetes manifest files from feature branch commits. Integrate with Config Sync to test new images in dynamically created GKE Dev clusters for each feature branch, which are deleted upon merge request.

Correct answer: C

Explanation

Option C is correct as it enables developers to test their features in isolated namespaces on the Dev GKE cluster, thus avoiding interference from other teams. Options A and D involve main branch merges or creating separate clusters for each feature branch, which may not be as cost-effective or stable. Option B does not provide isolation for testing, which is essential for resolving the developers' issues.