GCP Professional Cloud Architect Practice Question

Your organization runs dozens of microservices on Google Kubernetes Engine. For every code push, the team wants a fully managed workflow that 1) hosts Git repositories, 2) builds and unit-tests container images, 3) scans and stores those images in a private registry, and 4) rolls out updates progressively from staging to multiple production clusters with automatic rollback-all while avoiding custom scripting. Which combination of Google Cloud services will best implement this end-to-end SDLC pipeline?

Cloud Source Repositories for code, Cloud Composer to orchestrate builds, Container Registry for image storage, and a self-hosted Spinnaker on Compute Engine for deployments
GitHub Enterprise for code, Jenkins on GKE for CI, Container Registry for images, and Traffic Director for canary deployments
Cloud Storage buckets for source code, event-triggered Cloud Functions for builds, Artifact Registry for images, and Deployment Manager for rolling out to GKE
Cloud Source Repositories for code hosting, Cloud Build for build and test, Artifact Registry with vulnerability scanning for image storage, and Cloud Deploy for progressive GKE rollouts

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Answer Description

The required workflow maps cleanly onto four managed Google Cloud services: a private Git repository in Cloud Source Repositories handles source control; Cloud Build can be triggered on every commit to compile, run unit tests, and build container images; the finished images are pushed to Artifact Registry, which also performs Container Analysis-based vulnerability scanning; finally, Cloud Deploy pulls the approved image from Artifact Registry and executes promotion strategies such as progressive rollouts and automatic rollbacks across staging and production GKE targets. The other options either rely on self-managed components (Jenkins, Spinnaker) or services that do not natively provide the requested SDLC capabilities (Cloud Composer, Traffic Director, Cloud Functions, Deployment Manager).

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