GCP Professional Cloud Architect Practice Question

Your company is migrating a set of on-premises Kubernetes microservices to Google Cloud. The workloads include stateful services that mount persistent volumes, a GPU-accelerated image processor, and sidecar containers for logging. The platform team requires continued access to the Kubernetes API and the ability to choose VM machine types, yet wants Google to manage and patch the cluster control plane. Which Google Cloud compute service best meets these needs while minimizing operational effort?

Deploy the microservices on a regional Google Kubernetes Engine Standard cluster.
Use App Engine flexible environment with custom runtimes for every microservice.
Package each service as a container image and deploy to Cloud Run (fully managed).
Create a Compute Engine managed instance group running Container-Optimized OS instances that start the containers on boot.

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Answer Description

A regional Google Kubernetes Engine (GKE) Standard cluster delivers a fully managed control plane, so Google handles control-plane patching and availability. You still administer the Kubernetes API, pick node machine types (including GPU-enabled instances), deploy stateful workloads with PersistentVolumeClaims, and run sidecar containers-capabilities specifically designed for GKE.
Cloud Run removes node management but cannot mount persistent disks, does not support GPUs, and limits control over the Kubernetes API.
App Engine flexible can run Docker images but offers no direct Kubernetes interface, has an ephemeral filesystem, and lacks GPU support.
Compute Engine managed instance groups with Container-Optimized OS give control over VMs but leave you to operate Kubernetes or another orchestrator yourself, so they provide no managed control plane and increase operational overhead.

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