The correct answer is to deploy both model versions to the same Vertex AI Endpoint and adjust the traffic split settings. This works because Vertex AI Endpoints natively support traffic splitting between model versions, allowing you to route a percentage of inference requests—say, 10% to the new version and 90% to the stable one—without deploying a separate endpoint or managing complex routing logic. On the Google Cloud Generative AI Leader exam, this scenario tests your understanding of how the Model Registry integrates with Endpoints for safe, incremental rollouts; a common trap is assuming you need a separate endpoint for each version or that you must manually redirect traffic via a load balancer. The key memory tip is “one endpoint, many versions, split by percentage”—think of it like a water faucet with two hoses, where you simply turn the valve to control the flow to each hose, not build a new faucet.
Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
This Generative AI Leader practice question tests your understanding of google cloud's generative ai offerings. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
A company is using Vertex AI Model Registry to manage multiple versions of its custom generative model. They want to automatically route a percentage of traffic to a new model version for testing. What should they do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Deploy both versions to the same endpoint and adjust traffic split settings
Vertex AI Endpoints support traffic splitting between model versions.
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.
✗
Set up a Cloud Tasks queue to distribute requests
Why it's wrong here
Cloud Tasks is for async tasks, not real-time traffic splitting.
✗
Create a new endpoint for each version
Why it's wrong here
This would not allow automatic traffic splitting; manual routing is cumbersome.
✓
Deploy both versions to the same endpoint and adjust traffic split settings
Why this is correct
Vertex AI endpoints allow splitting traffic percentage across deployed models.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use a load balancer in front of the endpoints
Why it's wrong here
Load balancer is unnecessary; endpoint traffic split is built-in.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 Generative AI Leader exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What does this Generative AI Leader question test?
Google Cloud's Generative AI Offerings — This question tests Google Cloud's Generative AI Offerings — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Deploy both versions to the same endpoint and adjust traffic split settings — Vertex AI Endpoints support traffic splitting between model versions.
What should I do if I get this Generative AI Leader question wrong?
Identify which Generative AI Leader exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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