PCDOE Implementing service monitoring strategies Practice Question
You are a DevOps engineer for a SaaS company that provides a REST API. The API is deployed on Google Cloud Run. You have configured Cloud Monitoring alerts for 5xx errors. Recently, you received an alert that the error rate exceeded 5% for 5 minutes. You investigated and found that the errors were HTTP 503 (Service Unavailable) from a specific endpoint. The endpoint calls an internal Cloud SQL database. The database CPU utilization was at 90% during that period. You suspect the database is the bottleneck. Which action should you take to reduce the error rate without over-provisioning?
⚠ Common exam trap
Google Cloud often tests the misconception that scaling application instances (Cloud Run) is the default fix for backend bottlenecks, but the trap here is that increasing concurrency without addressing database connection limits can exacerbate the problem.
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
✓
Implement connection pooling and retry logic with exponential backoff in the API service
Implementing connection pooling and retry logic with exponential backoff directly addresses the database bottleneck without over-provisioning. Connection pooling reduces the number of concurrent connections to Cloud SQL, lowering CPU contention, while exponential backoff prevents thundering herd retries that could further overwhelm the database. This approach 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.
- ✓
Implement connection pooling and retry logic with exponential backoff in the API service
Why this is correct
This reduces the number of simultaneous connections to the database and handles transient failures gracefully.
- ✗
Increase the max instances per revision in Cloud Run to handle more concurrent requests
Why it's wrong here
Increasing Cloud Run instances could increase load on the already stressed database, worsening the issue.
- ✗
Reduce the min instances of Cloud Run to decrease load on the database
Why it's wrong here
Reducing instances may cause cold starts and does not address the root cause of database overload.
- ✗
Add a Cloud SQL read replica and route read queries to it
Why it's wrong here
The endpoint causing 503 errors likely involves writes; read replicas won't reduce write load.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCDOE 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 PCDOE exam.