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PMLE Practice Question: Set up monitoring for a Vertex AI model that…
You need to set up monitoring for a Vertex AI model that serves predictions in real-time. The model is expected to have a latency SLA of under 100ms. Which metric should you configure an alert on to ensure the SLA is met?
⚠ Common exam trap
Google Cloud often tests the misconception that median (p50) latency is sufficient for SLAs, but the trap is that SLAs require tail-latency guarantees (p99 or p999) to catch performance outliers that violate the threshold.
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
✓
p99 latency of prediction requests
P99 latency measures the worst-case latency experienced by 99% of requests, which is the standard metric for enforcing a strict SLA like under 100ms. Monitoring p99 ensures that even the slowest 1% of requests do not violate the threshold, providing a robust guarantee for real-time predictions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
p50 latency of prediction requests
Why it's wrong here
Median latency does not capture worst-case.
- ✗
Prediction drift score
Why it's wrong here
Unrelated to latency SLA.
- ✓
p99 latency of prediction requests
Why this is correct
p99 captures tail latency critical for SLA.
- ✗
Number of prediction requests per second
Why it's wrong here
Request count does not measure latency.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE 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 PMLE exam.