PCDOE Implementing service monitoring strategies Practice Question
A company has an application that experiences intermittent errors. They want to be notified immediately when the error rate exceeds 1% of total requests. What should they implement?
⚠ Common exam trap
Google Cloud often tests the distinction between monitoring availability (uptime checks) and monitoring error rates (log-based metrics), leading candidates to mistakenly choose uptime checks for error rate detection.
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
✓
Create a log-based metric counting error logs and set an alerting policy in Cloud Monitoring
The requirement is to be notified when the error rate exceeds 1% of total requests, which requires a metric that counts error logs relative to total requests. A log-based metric in Cloud Logging can filter for error log entries (e.g., status codes 5xx), and an alerting policy in Cloud Monitoring can trigger when the ratio of error logs to total requests surpasses 1%. This directly addresses the intermittent error rate condition with precise threshold-based alerting.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create an uptime check pointing to the application endpoint
Why it's wrong here
Uptime checks monitor availability, not error rate.
- ✓
Create a log-based metric counting error logs and set an alerting policy in Cloud Monitoring
Why this is correct
This directly monitors error rate from logs and alerts on threshold.
- ✗
Use Cloud Trace to analyze latency and set an alert on trace spans
Why it's wrong here
Cloud Trace is for latency analysis, not error rate.
- ✗
Create a dashboard showing error count over time
Why it's wrong here
A dashboard does not trigger notifications.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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