Google PCA Design and plan a cloud solution architecture Practice Question
A company runs a web application on Compute Engine instances behind a global HTTP(S) Load Balancer. The application uses Cloud SQL for MySQL for user data. Users report that during peak hours, the page load times increase significantly. The development team notices that the number of database connections exceeds the maximum allowed, causing some requests to fail. The application is designed to use connection pooling with a maximum pool size of 100 connections per instance. There are currently 10 instances. The Cloud SQL instance is configured with 4 vCPUs and 15 GB memory, and the maximum connections is set to 400. The application team wants to minimize cost while resolving the issue. What should the architect recommend?
⚠ Common exam trap
The trap is that candidates instinctively choose 'scale up the database' (Option B) because it sounds like the obvious fix, ignoring the explicit 'minimize cost' constraint and the fact that the pool size is the actual misconfiguration.
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
✓
Reduce the max pool size per instance to 40 connections.
With 10 instances each configured for a max pool of 100 connections, the theoretical peak is 1,000 connections — far exceeding Cloud SQL's 400-connection limit. Reducing the pool to 40 per instance yields a maximum of 400 connections, which fits within the limit and resolves the failures without any cost increase. This is the only option that addresses the root cause (over-provisioned pools) while honoring the 'minimize cost' constraint.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Reduce the max pool size per instance to 40 connections.
Why this is correct
Ten instances at 100 pooled connections each demand 1,000 connections, far exceeding the 400 limit. Lowering the pool to 40 caps demand at exactly 400, matching the configured maximum without resizing the costly Cloud SQL instance, directly resolving the connection exhaustion at minimum cost.
- ✗
Increase the Cloud SQL instance tier to have more vCPUs and memory.
Why it's wrong here
A larger tier raises the connection ceiling but leaves the 1,000-connection demand from ten pools of 100 unchanged, and it increases cost rather than minimising it. Scaling the tier is right when CPU or memory, not connection count, is the actual bottleneck.
- ✗
Implement connection pooling at the global HTTP(S) Load Balancer level.
Why it's wrong here
Global HTTP(S) Load Balancers operate at layer 7 and cannot pool database connections; they only route HTTP traffic to backends. Pooling must occur between the application and Cloud SQL. This option is tempting because load balancers distribute client connections, but that applies to inbound web traffic, not MySQL sessions.
- ✗
Use Cloud SQL Proxy with connection pooling.
Why it's wrong here
Cloud SQL Proxy provides authenticated, encrypted connectivity to the instance; it does not itself pool or multiplex database connections, so the 1,000-connection total remains. Cloud SQL Proxy is correct when you need IAM-based secure access from outside the VPC without authorised networks.
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Data Migration and Transfer Services
Key term
Load balancer
A load balancer is a device or software that distributes incoming network traffic across multiple servers so no single server gets overwhelmed.
Key term
HTTP
HTTP stands for Hypertext Transfer Protocol, the set of rules web browsers and servers use to communicate and transfer web pages over the internet.
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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
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