Google PCA Design and plan a cloud solution architecture Practice Question
A small development team is prototyping a containerized application on Google Cloud. They want the least operational overhead for running containers, automatic scaling based on incoming requests, and the ability to scale to zero when there is no traffic. They do not need Kubernetes APIs or custom networking. Which compute option should the architect recommend?
⚠ Common exam trap
The trap here is assuming that serverless containers require Kubernetes, when Cloud Run provides container execution without any cluster management.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Run services with request-based autoscaling
Cloud Run is a fully managed serverless platform for containers that scales automatically based on requests and can scale to zero when idle. It removes the need to manage clusters, nodes, or autoscaling policies, which directly addresses the team's desire for minimal operational overhead and cost efficiency during periods without traffic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Google Kubernetes Engine Autopilot cluster
Why it's wrong here
GKE Autopilot reduces node management but still requires Kubernetes manifests, services, and ingress configuration, and it is not designed to scale the cluster to zero. For a simple prototype without a need for Kubernetes APIs, it introduces unnecessary complexity and cost compared to a request-driven serverless container service.
- ✓
Cloud Run services with request-based autoscaling
Why this is correct
Cloud Run runs containers in a fully managed, request-driven environment, scales automatically with incoming requests, and can scale to zero when idle so the team pays nothing during quiet periods. It requires no cluster or node management and no Kubernetes expertise, making it the lowest-overhead fit for this prototype.
- ✗
Compute Engine managed instance groups with an autoscaler
Why it's wrong here
Managed instance groups run VMs and require the team to manage the OS, container runtime, and scaling policies, which is more operational overhead than a serverless container platform. They also do not scale to zero, so idle capacity remains billable, failing the requirement to minimize cost when there is no traffic.
- ✗
Cloud Functions with a container image as the deployment artifact
Why it's wrong here
Cloud Functions is event-driven and function-oriented, with constraints on runtime and request handling that make it less suitable for a general containerized application expecting HTTP request scaling. It also lacks some of the container lifecycle flexibility of Cloud Run, so it is not the best match for the stated prototype requirements.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PCA practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCA exam.