Google PCA Design and plan a cloud solution architecture Practice Question
A small startup wants to deploy a containerized web application that scales automatically and only charges for resources used. They have limited operational experience. Which compute solution should they choose?
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 (fully managed).
Cloud Run (fully managed) is the right choice because it runs containerized applications on a fully managed serverless platform that automatically scales instances up and down (including to zero) based on traffic, and it bills only for the CPU, memory, and request resources actually consumed. This matches the startup's needs: containers, automatic scaling, pay-per-use pricing, and minimal operational overhead since Google manages the underlying infrastructure. App Engine Standard with a custom runtime is more restrictive and less container-native, while GKE with a multi-node pool and Compute Engine with a managed instance group both require the team to manage clusters, nodes, or instances and typically incur costs for provisioned capacity even when idle, which does not fit a low-ops, usage-based model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
App Engine Standard Environment with a custom runtime.
Why it's wrong here
App Engine Standard runs sandboxed language runtimes, so a custom runtime still cannot host arbitrary container images the way this containerised app requires. It is tempting because App Engine scales to zero and bills per request, which suits stateless web apps — but only those built on supported runtimes, not portable containers.
- ✗
Google Kubernetes Engine (GKE) with a multi-node pool.
Why it's wrong here
GKE requires the startup to design node pools, cluster upgrades, networking and workload manifests, which exceeds their limited operational experience. It is tempting because GKE runs containers with autoscaling and consumption-based node billing, making it the right choice for teams already fluent in Kubernetes operations.
- ✗
Compute Engine with a managed instance group.
Why it's wrong here
A managed instance group scales VMs, not containers, so the startup must still build images, patch hosts and configure autoscaling policies themselves. It is tempting because MIGs offer automatic scaling and per-second billing, which suits lift-and-shift VM workloads — but not a containerised app needing minimal operational effort.
- ✓
Cloud Run (fully managed).
Why this is correct
Cloud Run is fully managed, scaling container instances to zero when idle, so billing follows actual request usage. It removes cluster and node management, matching the startup's limited operational experience while satisfying automatic scaling and pay-per-use.
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
Related to this question
Learn chapter
Google Cloud Compute Options Overview
Key term
Managed instance group
A managed instance group is a collection of identical virtual machine instances that are automatically managed as a single unit to ensure high availability and scalability.
Key term
GKE
GKE is Google's managed Kubernetes service that automates deploying, scaling, and managing containerized applications in the cloud.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.