Google PCA Practice Question: Analyze and optimize technical and business processes
A startup runs a web application on Google Kubernetes Engine (GKE) with 3 replicas serving user traffic. They use Cloud SQL for the database. Recently, the application experienced intermittent timeouts during peak hours. Monitoring shows high CPU usage on the GKE nodes and increased database connection pool exhaustion. The team is looking for a cost-effective solution that minimizes architectural changes. The application is stateless. What should they do?
⚠ Common exam trap
Google Cloud often tests the misconception that scaling compute resources (nodes or pods) alone fixes database connection issues, but the trap here is that connection pool exhaustion is a database-layer problem requiring a connection pooler, not just more application instances.
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 number of pod replicas and configure a connection pooler like PgBouncer for Cloud SQL
The application is stateless and experiencing database connection pool exhaustion alongside high CPU on GKE nodes. Increasing pod replicas distributes the CPU load across more pods, while adding a connection pooler like PgBouncer reduces the number of direct connections to Cloud SQL, preventing pool exhaustion without requiring database tier changes. This approach is cost-effective because it optimizes existing resources rather than scaling infrastructure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add more nodes to the GKE cluster and enable cluster autoscaling
Why it's wrong here
Adding nodes without increasing pods doesn't reduce CPU usage per node; connection pool issue remains.
- ✓
Increase the number of pod replicas and configure a connection pooler like PgBouncer for Cloud SQL
Why this is correct
More pods distribute CPU load, and a connection pooler reduces database connections, addressing both issues cost-effectively.
- ✗
Vertically scale the GKE node pool to larger machine types and increase Cloud SQL tier
Why it's wrong here
Vertical scaling is costly and may not solve connection pool exhaustion; also architectural change is minimal but not optimal.
- ✗
Set up a Cloud SQL read replica and route read queries to it
Why it's wrong here
Read replica does not reduce write connection pool exhaustion; also adds complexity and cost.
Go deeper
Related to this question
Learn chapter
Introduction to Google Cloud Platform
Key term
GKE
GKE is Google's managed Kubernetes service that automates deploying, scaling, and managing containerized applications in the cloud.
Key term
Pod
A pod is the smallest deployable unit in Kubernetes, containing one or more containers that share storage, network, and a specification for how to run.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.