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Monitoring ML SolutionseasyMultiple ChoiceObjective-mapped

PMLE Monitoring ML Solutions Practice Question

An ML engineer needs to monitor the error rate of prediction jobs on a Vertex AI Endpoint. Where can they view the number of failed prediction requests over time?

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

Cloud Monitoring

Vertex AI Endpoint metrics are integrated with Cloud Monitoring. Specific metrics like 'predictions/failed_count' can be viewed in Cloud Monitoring dashboards.

Answer analysis

Option-by-option breakdown

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

  • Cloud Monitoring

    Why this is correct

    Correct: Cloud Monitoring provides metrics and alerts for endpoint predictions.

  • Cloud Console endpoint details page

    Why it's wrong here

    The console shows basic stats but not historical error rate over time.

  • Vertex AI Experiments

    Why it's wrong here

    Experiments track training runs, not production errors.

  • Cloud Logging

    Why it's wrong here

    Logging shows logs, not aggregated metrics by default.

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JA

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.