- A
Enable Cloud SQL automatic storage increase.
Why wrong: Automatic storage increase helps with storage capacity, not CPU or connection limits.
- B
Increase the max connections parameter on Cloud SQL.
Why wrong: Increasing max connections can worsen CPU contention and does not address the root cause.
- C
Increase the Cloud SQL machine type to the next tier.
Why wrong: Increasing machine type adds cost and may be premature if read offloading suffices.
- D
Add read replicas and split read/write traffic.
Read replicas distribute read load, reducing primary database CPU and connection usage.
Google PCA Practice Question: Analyze and optimize technical and business processes
This PCA practice question tests your understanding of analyze and optimize technical and business processes. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company runs a customer-facing web application on Google Kubernetes Engine (GKE) in us-central1. The application uses a Cloud SQL for PostgreSQL database for user data. Recently, they noticed that during peak hours, the application response times increase significantly, and some requests time out. The team has already scaled the GKE nodepool to the maximum size, but the issue persists. Database CPU utilization is at 80%, and connections are near the max limit. The application uses connection pooling via PgBouncer running as a sidecar. The team suspects the database is the bottleneck. They need to improve performance with minimal cost impact. What should they do?
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
Add read replicas and split read/write traffic.
Option D is correct because adding read replicas and splitting read/write traffic offloads read queries from the primary Cloud SQL instance, reducing CPU and connection pressure. PgBouncer as a sidecar can be configured to route read-only transactions to replicas, while writes go to the primary. This directly addresses the 80% CPU and max connections issue without increasing costs as much as scaling up the machine type.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable Cloud SQL automatic storage increase.
Why it's wrong here
Automatic storage increase helps with storage capacity, not CPU or connection limits.
- ✗
Increase the max connections parameter on Cloud SQL.
Why it's wrong here
Increasing max connections can worsen CPU contention and does not address the root cause.
- ✗
Increase the Cloud SQL machine type to the next tier.
Why it's wrong here
Increasing machine type adds cost and may be premature if read offloading suffices.
- ✓
Add read replicas and split read/write traffic.
Why this is correct
Read replicas distribute read load, reducing primary database CPU and connection usage.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that scaling up (increasing machine type) is always the first step for database performance issues, when in fact read replicas with read/write splitting can be more cost-effective and scalable for read-heavy workloads.
Detailed technical explanation
How to think about this question
Cloud SQL read replicas use PostgreSQL streaming replication to maintain an asynchronously updated copy of the primary database. PgBouncer can be configured with separate connection pools for read/write and read-only traffic, using the `server_check_query` or `query` routing to direct SELECT statements to replicas. This pattern is common in high-read workloads and can reduce primary CPU by 40-60% in practice, while keeping costs linear with the number of replicas rather than exponential with machine tier upgrades.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Questions learners often ask
What does this PCA question test?
Analyze and optimize technical and business processes — This question tests Analyze and optimize technical and business processes — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add read replicas and split read/write traffic. — Option D is correct because adding read replicas and splitting read/write traffic offloads read queries from the primary Cloud SQL instance, reducing CPU and connection pressure. PgBouncer as a sidecar can be configured to route read-only transactions to replicas, while writes go to the primary. This directly addresses the 80% CPU and max connections issue without increasing costs as much as scaling up the machine type.
What should I do if I get this PCA question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 30, 2026
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.
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