GCP Professional Cloud Architect Practice Question

An online gaming startup plans to deploy eight stateless, containerized microservices that serve its public HTTP API. During live tournaments, request volume can surge by a factor of 20 within seconds, while traffic often drops to zero between events. The two-person operations team wants to avoid provisioning or patching any virtual machines or Kubernetes infrastructure. Each microservice must scale independently based on concurrent requests and be able to scale down to zero when idle. Which Google Cloud compute platform best meets these requirements?

Run each microservice in a managed instance group of Compute Engine VMs behind a global external HTTP load balancer.
Package the microservices as custom runtimes and deploy them to App Engine flexible environment.
Create a single GKE Autopilot cluster and configure Horizontal Pod Autoscalers with KEDA to scale each microservice.
Deploy each microservice as an independent Cloud Run service using container images stored in Artifact Registry.

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Answer Description

Cloud Run runs OCI-compliant container images on a fully managed serverless platform. It performs request-driven, per-service autoscaling that can add many container instances within seconds and automatically scales to zero after a period of idleness, eliminating idle-time costs. Because Google abstracts away all cluster and VM management, the two-person team has no operating-system or node patching responsibilities.

GKE Autopilot manages nodes, but you must still define Kubernetes objects and configure an add-on such as KEDA for scale-to-zero, adding complexity the team wants to avoid. App Engine flexible environment also removes OS-patching tasks, but its VM-based scaling typically takes minutes and never reaches zero instances, which could leave idle capacity running between tournaments. Managed instance groups on Compute Engine require creating and maintaining instance templates, images, and autoscaler settings; while Google patches the OS, the team would still oversee VM lifecycle and capacity planning. Therefore, Cloud Run is the best fit.

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