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Answer: 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 images in dynamically created namespaces on the Dev GKE cluster with autoscaling enabled. Implement a post-test namespace cleanup routine.
The question addresses the need for a cost-effective solution to isolate development testing environments in a shared GKE cluster to prevent dependency test failures and delayed releases. Option A suggests automating CI pipelines with Cloud Build for container image creation and Kubernetes manifest updates from main branch merge requests, integrating Config Sync for testing in dynamically created namespaces on the Dev GKE cluster with autoscaling, and implementing a post-test namespace cleanup. This approach isolates testing environments by namespace, which is cost-effective but may not fully isolate the testing environment from other development activities. Option B focuses on progressive delivery across environments using Cloud Deploy, which does not directly address the need for isolated testing environments in the Dev cluster. Option C is similar to Option A but updates Kubernetes manifest files from feature branch commits, which could introduce instability in the shared Dev cluster. Option D proposes creating and deleting GKE Dev clusters for each feature branch, which provides complete isolation but may not be the most cost-effective solution due to the overhead of cluster creation and deletion. The most cost-effective solution that provides adequate isolation is Option A, as it leverages namespaces for isolation within a single cluster, reducing overhead while still providing a stable environment for testing.
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Your company has a 12-microservice application running on Google Kubernetes Engine (GKE) with multiple teams working on features across Dev, Staging, and Production environments. Developers experience dependency test failures and release delays due to concurrent deployments from multiple feature branches in the shared Dev GKE cluster.
What cost-effective solution should you implement to provide developers with isolated, stable environments for testing microservice features without interference from other development activities?
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 images in dynamically created namespaces on the Dev GKE cluster with autoscaling enabled. Implement a post-test namespace cleanup routine.
B
Automate CI pipelines by using Cloud Build to create container images and update Kubernetes 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 environments.
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.