easyMultiple Choice
Google PCA Practice Question: A startup wants to deploy a containerised web…
A startup wants to deploy a containerised web application that auto-scales based on HTTP request traffic, with no infrastructure management. They expect unpredictable traffic spikes. Which compute service is most suitable?
⚠ Common exam trap
PCA often tests the distinction between serverless containers (Cloud Run) and serverless functions (Cloud Functions) — candidates wrongly pick Cloud Functions for 'containerised' workloads or GKE Autopilot when 'no infrastructure management' is the key phrase.
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 a fully managed serverless container platform that automatically scales container instances based on incoming HTTP requests (including scale-to-zero), requires no cluster or VM management, and is purpose-built for stateless containerised web workloads with unpredictable traffic. It handles HTTP load balancing, TLS, and concurrency tuning natively, matching the startup's requirements exactly.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Cloud Run
Why this is correct
Cloud Run is fully managed and scales container instances automatically from zero based on incoming HTTP request volume, so unpredictable spikes are absorbed without provisioning or managing servers. It satisfies the no-infrastructure-management and traffic-driven autoscaling constraints directly.
- ✗
Compute Engine with managed instance groups
Why it's wrong here
Managed instance groups require you to choose and patch the underlying VMs, so infrastructure management remains with the startup. It is tempting because autoscaling is built in, and would be correct when workloads need OS-level control or cannot be containerised.
- ✗
Cloud Functions
Why it's wrong here
Cloud Functions runs event-driven single-purpose functions, not a persistent containerised web application listening for HTTP traffic. It is tempting because it is fully serverless and scales automatically, and would be correct for short-lived, event-triggered code responding to Pub/Sub, storage or HTTP events.
- ✗
Google Kubernetes Engine (GKE) Autopilot
Why it's wrong here
GKE Autopilot still requires container orchestration concepts and cluster configuration, so it does not meet the no-infrastructure-management requirement. It is tempting for containerised workloads, and would be correct when teams need Kubernetes APIs, custom controllers or fine-grained pod scheduling.
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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Key term
Concurrency
Concurrency is the ability of a system to handle multiple tasks at the same time by dividing resources and switching between them efficiently.
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
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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.