This GCDL practice question tests your understanding of scaling with google cloud operations. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses Cloud Functions and notices that some functions are taking longer than expected. They want to identify which functions have the highest latency. What should they use?
Cloud Audit Logs
Why wrong: Audit logs record who did what, not function performance.
Error Reporting
Why wrong: Error Reporting handles application errors, not performance metrics.
Cloud Monitoring metrics
Cloud Monitoring collects metrics like execution time for Cloud Functions.
Cloud Logging queries
Why wrong: Logs show individual durations but are less efficient for aggregate latency analysis.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Cloud Monitoring metrics
Cloud Monitoring metrics, specifically the 'execution_time' metric for Cloud Functions, provide the precise latency data needed to identify functions with the highest execution duration. Unlike logs or error reports, metrics are designed for numerical aggregation and can be used to create dashboards or alerts that rank functions by their p50, p95, or p99 latency values.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Cloud Audit Logs
Why it's wrong here
Audit logs record who did what, not function performance.
Error Reporting
Why it's wrong here
Error Reporting handles application errors, not performance metrics.
Cloud Monitoring metrics
Why this is correct
Cloud Monitoring collects metrics like execution time for Cloud Functions.
Related concept
Read the scenario before looking for a memorised answer.
Cloud Logging queries
Why it's wrong here
Logs show individual durations but are less efficient for aggregate latency analysis.
Common exam traps
Google Cloud often tests the distinction between logs (Cloud Logging) and metrics (Cloud Monitoring), trapping candidates who think that because latency data appears in logs, querying logs is the correct method, when in fact metrics are the proper tool for numerical aggregation and ranking.
Trap categories for this question
Command / output trap
Logs show individual durations but are less efficient for aggregate latency analysis.
Detailed technical explanation
Cloud Functions automatically emit the 'execution_time' metric to Cloud Monitoring, which records the duration in milliseconds for each invocation. By using the Monitoring Query Language (MQL) or the Metrics Explorer, you can compute percentiles (e.g., p99) across all functions and sort them to identify the highest latency. This approach scales efficiently even with thousands of invocations, whereas querying logs for the same data would be slower and more expensive.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Scaling with Google Cloud operations — This question tests Scaling with Google Cloud operations — Read the scenario before looking for a memorised answer..
The correct answer is: Cloud Monitoring metrics — Cloud Monitoring metrics, specifically the 'execution_time' metric for Cloud Functions, provide the precise latency data needed to identify functions with the highest execution duration. Unlike logs or error reports, metrics are designed for numerical aggregation and can be used to create dashboards or alerts that rank functions by their p50, p95, or p99 latency values.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This GCDL 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 GCDL exam.
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