Question 235 of 500
Managing application performance monitoringeasyMultiple ChoiceObjective-mapped

PCD Managing application performance monitoring Practice Question

This PCD practice question tests your understanding of managing application performance monitoring. 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.

Exhibit

fetch gce_instance
| metric 'compute.googleapis.com/instance/cpu/utilization'
| filter metric.utilization > 0.9
| align mean(5m)
| every 5m

Refer to the exhibit. You are reviewing a Cloud Monitoring MQL query. What is the purpose of this query?

Question 1easymultiple choice
Full question →

Exhibit

fetch gce_instance
| metric 'compute.googleapis.com/instance/cpu/utilization'
| filter metric.utilization > 0.9
| align mean(5m)
| every 5m

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

It filters for instances with CPU utilization > 90% and then computes the 5-minute average.

Option D is correct because the MQL query uses the `filter` clause to first select only time series where `cpu.utilization` exceeds 90%, and then applies the `avg` aggregation over a 5-minute window. This order of operations ensures that the average is computed only on the filtered data points, not on all instances.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • It displays the raw CPU utilization data points that exceed 90%.

    Why it's wrong here

    The query includes an align step, so it does not display raw data.

  • It shows the 5-minute average CPU utilization for all instances, then filters out those with average > 90%.

    Why it's wrong here

    The filter is applied before the alignment, not after.

  • It computes the 5-minute average of CPU utilization and then selects instances where any data point exceeded 90%.

    Why it's wrong here

    The filter is on raw data before alignment.

  • It filters for instances with CPU utilization > 90% and then computes the 5-minute average.

    Why this is correct

    Filter first, then align, as shown in the query order.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Cisco often tests the order of operations in MQL queries, specifically whether the filter or aggregation is applied first, leading candidates to confuse the sequence and misinterpret the query's purpose.

Detailed technical explanation

How to think about this question

In Cloud Monitoring MQL, the `filter` operation is applied to the time series before any aggregation, meaning it selects only the data points that meet the condition. The `avg` function then computes the mean of those selected points over the specified window. This is distinct from SQL-like WHERE clauses that filter after aggregation, and it allows for precise control over which data contributes to the metric.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.

What to study next

Got this wrong? Here's your next step.

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

Questions learners often ask

What does this PCD question test?

Managing application performance monitoring — This question tests Managing application performance monitoring — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: It filters for instances with CPU utilization > 90% and then computes the 5-minute average. — Option D is correct because the MQL query uses the `filter` clause to first select only time series where `cpu.utilization` exceeds 90%, and then applies the `avg` aggregation over a 5-minute window. This order of operations ensures that the average is computed only on the filtered data points, not on all instances.

What should I do if I get this PCD question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 25, 2026

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This PCD 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 PCD exam.