- A
Configure feature monitoring in the feature view with a drift threshold of 0.1 using Jensen-Shannon divergence
Vertex AI Feature Store allows setting drift thresholds per feature view, using methods like JS divergence.
- B
Use BigQuery scheduled queries to compare distributions and send alerts
Why wrong: This is a manual approach; Vertex AI Feature Store provides built-in monitoring.
- C
Set up a Cloud Composer DAG to compute drift and publish to Cloud Monitoring
Why wrong: While possible, it's not the native approach; Feature Store monitoring is simpler.
- D
Enable model monitoring on the Vertex AI endpoint to detect drift
Why wrong: Model monitoring detects drift on prediction inputs, not features in the feature store.
Question 496 of 1,000
Collaborating Within and Across Teams to Manage Data and Models →mediumMultiple ChoiceObjective-mapped
PMLE Practice Question: Collaborating Within and Across Teams to Manage Data and Models
This PMLE practice question tests your understanding of collaborating within and across teams to manage data and models. 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.
You are setting up feature monitoring in Vertex AI Feature Store to detect drift in a numerical feature. The monitoring job should run daily and alert if the Jensen-Shannon divergence exceeds 0.1. Which configuration should you use?
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
✓
Configure feature monitoring in the feature view with a drift threshold of 0.1 using Jensen-Shannon divergence
Feature monitoring in Vertex AI Feature Store uses monitoring_config with drift detection via statistical tests like Jensen-Shannon divergence. The correct approach is to set the drift threshold in the feature view's monitoring configuration.
Key principle: Authentication proves identity; authorization controls what that identity can do after login. Both must work for full privileged access.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure feature monitoring in the feature view with a drift threshold of 0.1 using Jensen-Shannon divergence
Why this is correct
Vertex AI Feature Store allows setting drift thresholds per feature view, using methods like JS divergence.
Related concept
Authentication checks who the user is.
- ✗
Use BigQuery scheduled queries to compare distributions and send alerts
Why it's wrong here
This is a manual approach; Vertex AI Feature Store provides built-in monitoring.
- ✗
Set up a Cloud Composer DAG to compute drift and publish to Cloud Monitoring
Why it's wrong here
While possible, it's not the native approach; Feature Store monitoring is simpler.
- ✗
Enable model monitoring on the Vertex AI endpoint to detect drift
Why it's wrong here
Model monitoring detects drift on prediction inputs, not features in the feature store.
Common exam traps
Common exam trap: authentication is not authorization
Logging in proves the user can authenticate. It does not automatically mean the user is allowed to enter privileged or configuration mode. Watch for AAA authorization, privilege level and command authorization details.
Detailed technical explanation
How to think about this question
This kind of question is testing the difference between identity and permission. A user may successfully log in to a router because authentication is working, but still fail to enter configuration mode because authorization is missing, misconfigured or mapped to a lower privilege level.
KKey Concepts to Remember
- Authentication checks who the user is.
- Authorization controls what the user is allowed to do after login.
- Privilege levels affect access to EXEC and configuration commands.
- AAA, TACACS+ and RADIUS can separate login success from command access.
TExam Day Tips
- Do not assume successful login means full administrative access.
- Look for words such as cannot enter configuration mode, privilege level, authorization or command access.
- Separate login problems from permission problems before choosing the answer.
Key takeaway
Authentication proves identity; authorization controls what that identity can do after login. Both must work for full privileged access.
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.
Review Cisco AAA concepts — authentication, authorization, and accounting. Study privilege levels (0–15), command authorization under TACACS+, and how RADIUS differs. Then practise related PMLE questions on access control and AAA configuration.
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Collaborating Within and Across Teams to Manage Data and Models — study guide chapter
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FAQ
Questions learners often ask
What does this PMLE question test?
Collaborating Within and Across Teams to Manage Data and Models — This question tests Collaborating Within and Across Teams to Manage Data and Models — Authentication checks who the user is..
What is the correct answer to this question?
The correct answer is: Configure feature monitoring in the feature view with a drift threshold of 0.1 using Jensen-Shannon divergence — Feature monitoring in Vertex AI Feature Store uses monitoring_config with drift detection via statistical tests like Jensen-Shannon divergence. The correct approach is to set the drift threshold in the feature view's monitoring configuration.
What should I do if I get this PMLE question wrong?
Review Cisco AAA concepts — authentication, authorization, and accounting. Study privilege levels (0–15), command authorization under TACACS+, and how RADIUS differs. Then practise related PMLE questions on access control and AAA configuration.
What is the key concept behind this question?
Authentication checks who the user is.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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