PMLE Monitoring ML Solutions Practice Question
A company wants to monitor the cost of their Vertex AI prediction endpoint. They are charged per hour per replica and per request for GPU instances. Which approach should they use to track these costs?
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
✓
Set up Cloud Billing budget alerts and export billing data to BigQuery for analysis
Vertex AI prediction costs are tracked via Cloud Billing. Budget alerts can be set up to notify when spending exceeds a threshold. Cost breakdown can be viewed in the Billing reports.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set up Cloud Billing budget alerts and export billing data to BigQuery for analysis
Why this is correct
Budget alerts and exporting billing data are standard practices for cost monitoring.
- ✗
Use Vertex AI Model Monitoring to track cost metrics
Why it's wrong here
Model Monitoring does not track costs.
- ✗
Enable Cloud Monitoring dashboards for cost metrics
Why it's wrong here
Cloud Monitoring does not directly track costs; billing data is separate.
- ✗
Use Vertex AI Pipelines to track cost per job
Why it's wrong here
Pipelines track training costs but not online prediction costs.
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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.