Google PCA Practice Question: Managing and Provisioning a Solution Infrastructure
You want to monitor the latency of an application running on Compute Engine and create an alert if the 99th percentile latency exceeds 500ms for more than 5 minutes. Which approach should you use?
⚠ Common exam trap
PCA often tests the confusion between monitoring and tracing tools, where candidates might choose Cloud Trace for alerting because it deals with latency, but it lacks native alerting capabilities.
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 Metric Threshold alert using the 'Latency' metric with a percentile alignment
To monitor latency and alert on the 99th percentile exceeding 500ms for more than 5 minutes, you should create a Metric Threshold alert in Cloud Monitoring using the appropriate latency metric (e.g., from a load balancer or application) with a percentile alignment. This allows you to aggregate latency data over a window and trigger an alert when the condition is met.
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 Cloud Trace to analyze latency and set a trace-based alert
Why it's wrong here
Cloud Trace collects distributed traces for latency analysis but cannot evaluate a 99th percentile threshold over a five-minute window or fire alerts. Trace suits diagnosing where latency originates; alerting on percentile latency requires a Cloud Monitoring metric with an alerting policy.
- ✗
Use Error Reporting to capture latency errors
Why it's wrong here
Error Reporting aggregates application exceptions and stack traces, not request latency, so it cannot compute a 99th percentile or trigger on 500ms. It is tempting because it also monitors Compute Engine workloads, but it is the correct tool for triaging recurring errors, not latency thresholds.
- ✓
Create a Metric Threshold alert using the 'Latency' metric with a percentile alignment
Why this is correct
A metric threshold alert with percentile alignment computes the 99th percentile latency over the window and fires when it exceeds 500ms for more than 5 minutes. This directly matches the stated latency percentile and duration condition on the Compute Engine application.
- ✗
Create a log-based metric from application logs and set an alert on that metric
Why it's wrong here
Log-based metrics capture counts or extracted values from log entries, not the distribution of request latencies, so a 99th percentile cannot be computed from them. They suit alerting on error strings or event frequencies; latency percentiles require a distribution metric such as those from Cloud Monitoring or OpenTelemetry.
Go deeper
Related to this question
Learn chapter
Google Cloud Compute Options Overview
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Alerting policy
An alerting policy is a set of rules that defines when to send notifications about a system condition that needs attention.
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JA
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
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.