Google PCA Connection pooling Practice Question
An e-commerce platform uses Cloud SQL for PostgreSQL to serve product catalog data. As traffic grows, the database experiences high connection overhead and latency spikes. The team wants to reduce connection overhead and improve performance without changing application code. Which solution should they implement?
⚠ Common exam trap
Candidates may assume that increasing max connections solves connection overhead, but it actually increases contention. Connection pooling reuses connections, reducing overhead.
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
✓
Use Memorystore (Redis) to cache database queries.
Memorystore (Redis) caches database query results, reducing the number of queries hitting Cloud SQL. This lowers connection overhead because fewer connections are opened, and improves latency by serving repeated queries from an in-memory cache. No application code changes are needed if the caching layer is deployed as an intermediary. Option C is incorrect because Cloud SQL Auth Proxy only provides secure connectivity and does not perform connection pooling; a dedicated pooler like PgBouncer would be required.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Memorystore (Redis) to cache database queries.
Why this is correct
Memorystore (Redis) caches query results, reducing database load, but does not address connection overhead. Caching is not the solution to high connection overhead.
- ✗
Migrate to Cloud Spanner for better scalability.
Why it's wrong here
Cloud Spanner offers horizontal scalability, but migrating would require significant application changes and does not specifically reduce connection overhead.
- ✗
Use Cloud SQL Auth Proxy with connection pooling enabled.
Why it's wrong here
Using Cloud SQL Auth Proxy with connection pooling enabled (via PgBouncer) reduces connection overhead by reusing connections and providing secure access without application code changes.
- ✗
Increase the maximum connections setting in Cloud SQL to handle more concurrent connections.
Why it's wrong here
Increasing the maximum connections setting allows more concurrent connections but does not reduce overhead; it can worsen performance if connections are created and destroyed frequently.
Go deeper
Related to this question
Learn chapter
Introduction to Google Cloud Platform
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Memorystore
A fully managed in-memory data store service that provides Redis and Memcached for caching, session storage, and real-time data processing.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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