- A
The alert condition is using the average aggregation with a short alignment period.
A short alignment period makes the alert sensitive to brief spikes, causing false positives.
- B
The threshold is set too low compared to actual CPU usage.
Why wrong: A low threshold would cause alerts when CPU is genuinely high, not false positives.
- C
The metric is being duplicated because multiple agents are running.
Duplicate metrics can cause the aggregate CPU metric to exceed the threshold even if real usage is low.
- D
The alerting policy was created in a different project and not imported.
Why wrong: Policies are per project; cross-project imports are not automatic but do not cause false positives.
- E
The VM is reporting metrics from a custom namespace instead of the standard agent.
Why wrong: Custom namespace would not affect standard CPU alerts; it would be a different metric.
PCDOE Implementing service monitoring strategies Practice Question
This PCDOE practice question tests your understanding of implementing service monitoring strategies. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
An alerting policy for high CPU utilization on a VM is firing even when CPU is not high. The team suspects a misconfiguration. Which two possible issues should they check? (Choose two.)
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
The alert condition is using the average aggregation with a short alignment period.
Option A is correct because using a short alignment period with average aggregation can cause the alert to fire on brief spikes in CPU utilization that do not represent sustained high usage. If the alignment period is too short (e.g., 1 minute), the alerting policy may trigger on transient bursts, even when the overall CPU load is low. This is a common misconfiguration in Google Cloud Monitoring (formerly Stackdriver) where the alignment period and aggregator settings must match the expected workload pattern.
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.
- ✓
The alert condition is using the average aggregation with a short alignment period.
Why this is correct
A short alignment period makes the alert sensitive to brief spikes, causing false positives.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
The threshold is set too low compared to actual CPU usage.
Why it's wrong here
A low threshold would cause alerts when CPU is genuinely high, not false positives.
- ✓
The metric is being duplicated because multiple agents are running.
Why this is correct
Duplicate metrics can cause the aggregate CPU metric to exceed the threshold even if real usage is low.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
The alerting policy was created in a different project and not imported.
Why it's wrong here
Policies are per project; cross-project imports are not automatic but do not cause false positives.
- ✗
The VM is reporting metrics from a custom namespace instead of the standard agent.
Why it's wrong here
Custom namespace would not affect standard CPU alerts; it would be a different metric.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that a low threshold (Option B) is the cause of false positives, but the real issue is the alignment period and aggregation settings that amplify transient spikes, not the threshold value itself.
Detailed technical explanation
How to think about this question
In Google Cloud Monitoring, the alignment period defines the window over which metric data points are combined using an aggregator (e.g., mean, max, min). A short alignment period (e.g., 60 seconds) with average aggregation can produce a metric series that is highly sensitive to short-lived CPU spikes, leading to alert fires even when the 95th percentile or sustained load is low. For production workloads, a longer alignment period (e.g., 5 minutes) combined with a higher percentile aggregator (e.g., 99th percentile) is often used to reduce noise and avoid false positives.
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.
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FAQ
Questions learners often ask
What does this PCDOE question test?
Implementing service monitoring strategies — This question tests Implementing service monitoring strategies — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The alert condition is using the average aggregation with a short alignment period. — Option A is correct because using a short alignment period with average aggregation can cause the alert to fire on brief spikes in CPU utilization that do not represent sustained high usage. If the alignment period is too short (e.g., 1 minute), the alerting policy may trigger on transient bursts, even when the overall CPU load is low. This is a common misconfiguration in Google Cloud Monitoring (formerly Stackdriver) where the alignment period and aggregator settings must match the expected workload pattern.
What should I do if I get this PCDOE 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.
About these practice questions
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Last reviewed: Jun 30, 2026
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.
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