The answer is to increase the duration to 30 minutes. This adjustment directly reduces false positive latency alerts by requiring the prediction latency to exceed 500 ms for a longer continuous window, filtering out brief, transient spikes that trigger the current 5-minute threshold. On the Google Professional Machine Learning Engineer exam, this tests your understanding of alerting policy configuration for model monitoring, specifically how tuning the duration parameter balances sensitivity against noise. A common trap is choosing to lower the threshold or adjust the lookback window, which would worsen false positives; instead, remember that increasing duration acts as a noise filter for sustained issues. Memory tip: think of it as a "patience window"—the longer you wait, the more confident you are that the latency problem is real, not a fluke.
PMLE Monitoring ML solutions Practice Question
This PMLE practice question tests your understanding of monitoring ml solutions. 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.
Refer to the exhibit. An alert policy is configured to trigger when prediction latency exceeds 500 ms for 5 consecutive minutes. The team is experiencing many false positive alerts during brief latency spikes. Which adjustment would most effectively reduce false positives while still detecting prolonged latency issues?
Why wrong: Changing to 'less than' would invert the alert, triggering when latency is low, which is not the intent.
B
Add a condition that CPU utilization is also high
Why wrong: Adding a CPU condition might reduce false positives if latency spikes are not CPU-related, but it may also cause missed detections if high latency occurs without high CPU.
C
Increase the duration to 30 minutes
A longer duration means the condition must persist for 30 minutes, filtering out brief spikes while still catching sustained high latency.
D
Increase the threshold to 1000 ms
Why wrong: Raising the threshold would reduce false positives but also miss true positives where latency is between 500 and 1000 ms but sustained.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the duration to 30 minutes
Increasing the duration from 5 to 30 minutes (Option C) directly addresses the problem of false positives from brief latency spikes by requiring the latency to exceed 500 ms for a longer continuous period before triggering an alert. This ensures that only sustained, prolonged latency issues—not transient spikes—activate the policy, aligning with the goal of detecting genuine degradation while ignoring noise.
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.
✗
Change the comparison to less than
Why it's wrong here
Changing to 'less than' would invert the alert, triggering when latency is low, which is not the intent.
✗
Add a condition that CPU utilization is also high
Why it's wrong here
Adding a CPU condition might reduce false positives if latency spikes are not CPU-related, but it may also cause missed detections if high latency occurs without high CPU.
✓
Increase the duration to 30 minutes
Why this is correct
A longer duration means the condition must persist for 30 minutes, filtering out brief spikes while still catching sustained high latency.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the threshold to 1000 ms
Why it's wrong here
Raising the threshold would reduce false positives but also miss true positives where latency is between 500 and 1000 ms but sustained.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between threshold and duration adjustments, trapping candidates who think raising the threshold (Option D) is the only way to reduce false positives, when in fact increasing the evaluation window is more precise for filtering out transient spikes without compromising detection of sustained issues.
Detailed technical explanation
How to think about this question
In monitoring systems like Amazon CloudWatch or Google Cloud Monitoring, alert policies evaluate metric streams over sliding windows; increasing the evaluation period (duration) reduces sensitivity to transient anomalies by requiring more consecutive high-latency data points. This approach leverages the concept of 'm-of-n' or 'consecutive breaches' logic, where a longer duration ensures statistical significance before triggering, effectively acting as a low-pass filter on the metric signal. Real-world ML inference pipelines often experience latency spikes due to cold starts or garbage collection pauses, which are brief and self-correcting, so a longer duration prevents unnecessary pager rotations while still catching sustained degradation from resource exhaustion or model drift.
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
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
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.
Monitoring ML solutions — This question tests Monitoring ML solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the duration to 30 minutes — Increasing the duration from 5 to 30 minutes (Option C) directly addresses the problem of false positives from brief latency spikes by requiring the latency to exceed 500 ms for a longer continuous period before triggering an alert. This ensures that only sustained, prolonged latency issues—not transient spikes—activate the policy, aligning with the goal of detecting genuine degradation while ignoring noise.
What should I do if I get this PMLE 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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