Google PCA Practice Question: Analysing and Optimising Technical and Business Processes
You are the architect for a company that runs a three-tier web application on Compute Engine. The CTO wants to reduce the monthly cloud bill without impacting performance or availability. You review the billing export in BigQuery and notice that the VMs are sized for peak load, but CPU utilization rarely exceeds 20% on weekdays and 5% on weekends. The application is stateless and uses an external Cloud SQL database. Which cost optimization strategy should you implement first?
⚠ Common exam trap
The trap here is assuming that committed use discounts or long-term commitments are the primary cost optimization, when in fact they should be applied only after right-sizing.
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
✓
Create a managed instance group with autoscaling and right-size the instance template based on actual utilization.
The application is stateless and overprovisioned, so the most effective first step is to right-size instances and use autoscaling to match capacity to demand. This reduces cost while maintaining performance and availability. Committed use discounts and long-term commitments only make sense after you have optimized the instance shape and quantity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a managed instance group with autoscaling and right-size the instance template based on actual utilization.
Why this is correct
This directly addresses the overprovisioning by scaling the number of instances to match demand and using a smaller machine type that fits actual CPU usage. It maintains availability because the managed instance group can span zones and replace unhealthy instances, and it does not require application changes since the app is stateless.
- ✗
Purchase a 3-year commitment for the current VM sizes.
Why it's wrong here
A long-term commitment locks in the current, oversized configuration. If you later right-size, you may still pay for the committed vCPUs and memory. This is the opposite of optimizing; you should first determine the correct size and then apply commitments to the steady-state baseline if appropriate.
- ✗
Move the application to Cloud Run.
Why it's wrong here
Cloud Run is a serverless container platform that can reduce costs for spiky workloads, but migrating a three-tier application requires containerization and may introduce cold starts or architectural changes. The scenario does not state that the application is container-ready, and the immediate goal is to optimize the existing Compute Engine footprint.
- ✗
Enable committed use discounts for the VMs.
Why it's wrong here
Committed use discounts reduce the cost of existing VM usage but do not address the underlying overprovisioning. Since utilization is very low, you would still be paying for idle capacity. The first step should be right-sizing; only after you have the correct shape should you consider commitments for the remaining baseline.
Go deeper
Related to this question
Learn chapter
Load Balancing and Autoscaling
Key term
Cloud SQL
Cloud SQL is a fully managed relational database service that lets you set up, maintain, and scale SQL databases (like MySQL, PostgreSQL, and SQL Server) in the cloud without managing the underlying infrastructure.
Key term
Compute Engine
Compute Engine is Google Cloud's Infrastructure-as-a-Service (IaaS) offering that lets you create and run virtual machines on Google's infrastructure.
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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.