Google PCA Practice Question: Managing and Provisioning a Solution Infrastructure
A startup wants to deploy a containerized web application that must scale automatically based on incoming request concurrency. The team wants to avoid managing Kubernetes nodes or clusters and prefers a fully managed serverless platform with per-request billing. Which Google Cloud service should the architect recommend?
⚠ Common exam trap
The trap here is treating GKE Autopilot as serverless and per-request, when it still bills for cluster infrastructure and targets Kubernetes workloads rather than request-driven container scaling.
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
Cloud Run is the managed serverless container platform that scales on request concurrency, scales to zero, and bills per request, with no cluster or node administration. It accepts standard container images, so the startup can deploy its existing artifact directly while gaining automatic scaling and usage-based pricing that the other options cannot provide.
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
Why it's wrong here
GKE Autopilot removes node management, but it still provisions and bills for cluster infrastructure and is oriented toward Kubernetes workloads rather than per-request serverless scaling. It does not match the requirement to avoid managing clusters or to pay purely per request.
- ✓
Cloud Run
Why this is correct
Cloud Run runs containers on a fully managed serverless platform, scales automatically based on request concurrency, scales to zero when idle, and bills per request and resource usage. It requires no cluster or node management, which aligns exactly with the startup's stated constraints for this web application.
- ✗
Compute Engine managed instance group with autoscaling
Why it's wrong here
A managed instance group autoscales VMs, but the team must still manage operating systems, patches, and capacity, and billing is per VM-hour rather than per request. This conflicts with the desire to avoid infrastructure management and to pay only for requests served.
- ✗
App Engine standard environment
Why it's wrong here
App Engine standard is a fully managed serverless platform, but it runs language-specific runtimes rather than arbitrary containers in the way Cloud Run does. For a containerized web application with concurrency-based scaling and per-request billing, Cloud Run is the more direct fit.
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 |
Go deeper
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Google Cloud Compute Options Overview
Key term
CAN
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Key term
Anthos
Anthos is a Google Cloud platform that lets you run applications consistently across different computing environments, like on-premises data centers and multiple public clouds.
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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.