Google PCA Practice Question: Analyze and optimize technical and business processes
A company migrated their on-premises database to Cloud SQL and now experiences high latency for read-heavy workloads. How can they optimize performance?
⚠ Common exam trap
Google Cloud often tests the misconception that vertical scaling (higher machine type) is the universal fix for performance issues, but the trap here is that read-heavy workloads require horizontal scaling via read replicas to distribute the read load, not just a more powerful single instance.
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.
Adding read replicas is the correct optimization because Cloud SQL read replicas offload read traffic from the primary instance, reducing latency for read-heavy workloads. Read replicas asynchronously replicate data from the primary using MySQL or PostgreSQL native replication, allowing queries to be distributed across multiple instances. This directly addresses the high latency by scaling read capacity horizontally without impacting write performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to a higher machine type.
Why it's wrong here
A higher machine type adds CPU and memory, but read-heavy Cloud SQL latency stems from disk I/O and query patterns, so the fix is read replicas or caching. It is tempting because vertical scaling is the default on-premises remedy, and it would be correct when the instance is genuinely CPU- or memory-bound.
- ✗
Enable automatic storage increase.
Why it's wrong here
Automatic storage increase only grows disk capacity when space runs low; it does not add memory or reduce disk I/O, so read latency is unchanged. It is tempting because it removes manual capacity planning, and would be the right choice for a database repeatedly hitting its storage limit.
- ✗
Use connection pooling.
Why it's wrong here
Connection pooling reuses database connections, cutting the overhead of repeatedly establishing them; it does not reduce the latency of the read queries themselves. It is tempting because pooling is a standard performance measure, and would be the right choice when connection churn, not query execution, is the bottleneck.
- ✓
Add read replicas.
Why this is correct
Read replicas serve read-only queries from separate database instances, offloading SELECT traffic from the primary. Distributing read-heavy workloads across replicas reduces contention and latency on the primary instance, directly addressing the high read latency described after the Cloud SQL migration.
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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.