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Google PCA Practice Question: An e-commerce company uses Cloud SQL for MySQL…
An e-commerce company uses Cloud SQL for MySQL for their transactional database. During a recent load test, the database experienced high latency under write-heavy workloads. The team needs to improve write performance without changing the application. Which action is most effective?
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
✓
Increase the machine type of the primary instance
Cloud SQL for MySQL supports read replicas for read scalability, but for write-heavy workloads you need a larger machine type (scale up) or use memory optimized. Adding read replicas does not help writes. Enabling binary logging adds overhead. Vertically scaling (increasing vCPUs and RAM) directly improves write throughput. Using Cloud Spanner would require application changes.
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 binary logging to improve write performance
Why it's wrong here
Binary logging records changes for replication and point-in-time recovery, adding write overhead rather than reducing it. It is tempting because it is a write-related setting, but it is enabled to support replicas or backups, not to improve transactional write throughput.
- ✓
Increase the machine type of the primary instance
Why this is correct
Increasing the primary instance's machine type adds vCPUs and memory, raising write throughput and InnoDB buffer pool capacity so dirty pages flush less often. This directly relieves the write-heavy latency bottleneck while requiring no application changes, satisfying the stem's constraint of improving write performance transparently.
- ✗
Migrate to Cloud Spanner
Why it's wrong here
Cloud Spanner requires schema and application changes to exploit its distributed architecture, so it fails the no-application-change constraint; Cloud SQL already offers the needed write throughput. Spanner suits globally distributed, horizontally scaling transactional workloads needing strong consistency across regions, not a single-region MySQL latency fix.
- ✗
Add multiple read replicas
Why it's wrong here
Read replicas serve read traffic only; writes still go to the primary instance, so write-heavy latency is unchanged. They are tempting because they scale read throughput well, and would be correct if the workload were read-heavy rather than dominated by writes.
Go deeper
Related to this question
Learn chapter
Resource Monitoring and Logging with Cloud Operations
Key term
Latency
Latency is the time delay between a request being sent over a network and the response being received, often measured in milliseconds.
Key term
Spanner
Google Cloud's globally distributed, strongly consistent, and horizontally scalable database service designed for mission-critical, transactional workloads.
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