- A
Use Vertex AI Experiments to run an A/B test between the two versions.
Why wrong: Experiments are for training, not serving traffic splitting.
- B
Deploy the new version to a separate endpoint and update your client to use the new endpoint for a percentage of requests.
Why wrong: This introduces client-side complexity and does not leverage Vertex AI's built-in traffic splitting.
- C
Update the endpoint to split traffic between the two model versions using the traffic split configuration.
Vertex AI traffic split allows gradual shifting of traffic between model versions on the same endpoint.
- D
Delete the old version and redeploy the new version with a different endpoint name, then update DNS.
Why wrong: This causes downtime and does not allow gradual traffic shifting.
PMLE Serving and Scaling Models Practice Question
This PMLE practice question tests your understanding of serving and scaling 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 deploy a new version of a model to a Vertex AI endpoint and want to gradually shift traffic from the old version to the new version over 24 hours. The endpoint currently serves 100% traffic to the old version. What should you do?
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
Update the endpoint to split traffic between the two model versions using the traffic split configuration.
Option C is correct because Vertex AI endpoints support a built-in traffic split configuration that allows you to gradually shift traffic between model versions deployed to the same endpoint. By updating the endpoint's traffic split percentages (e.g., from 100% old / 0% new to 0% old / 100% new over 24 hours), you can achieve a smooth, controlled rollout without changing client code or managing multiple endpoints.
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.
- ✗
Use Vertex AI Experiments to run an A/B test between the two versions.
Why it's wrong here
Experiments are for training, not serving traffic splitting.
- ✗
Deploy the new version to a separate endpoint and update your client to use the new endpoint for a percentage of requests.
Why it's wrong here
This introduces client-side complexity and does not leverage Vertex AI's built-in traffic splitting.
- ✓
Update the endpoint to split traffic between the two model versions using the traffic split configuration.
Why this is correct
Vertex AI traffic split allows gradual shifting of traffic between model versions on the same endpoint.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Delete the old version and redeploy the new version with a different endpoint name, then update DNS.
Why it's wrong here
This causes downtime and does not allow gradual traffic shifting.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google often tests the misconception that traffic splitting requires separate endpoints or client-side logic, when in fact Vertex AI provides a native traffic split configuration on a single endpoint.
Detailed technical explanation
How to think about this question
Vertex AI endpoints use a traffic split mechanism that leverages the underlying load balancer to route a percentage of requests to each model version based on the configured weights. The traffic split is applied at the endpoint level, meaning the same endpoint URL serves both versions, and the split can be updated incrementally (e.g., via the gcloud ai endpoints update command or the REST API) without downtime. A real-world scenario is canary deployments, where you start with 5% traffic to the new version, monitor for errors, and gradually increase to 100%.
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.
TExam Day Tips
- 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Serving and Scaling Models — study guide chapter
Learn the concepts, then practise the questions
- →
Serving and Scaling Models practice questions
Targeted practice on this topic area only
- →
All PMLE questions
1,000 questions across all exam domains
- →
Google Professional Machine Learning Engineer study guide
Full concept coverage aligned to exam objectives
- →
PMLE practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related PMLE practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Automating and Orchestrating ML Pipelines practice questions
Practise PMLE questions linked to Automating and Orchestrating ML Pipelines.
Collaborating Within and Across Teams to Manage Data and Models practice questions
Practise PMLE questions linked to Collaborating Within and Across Teams to Manage Data and Models.
Serving and Scaling Models practice questions
Practise PMLE questions linked to Serving and Scaling Models.
Monitoring ML Solutions practice questions
Practise PMLE questions linked to Monitoring ML Solutions.
Architecting Low-Code ML Solutions practice questions
Practise PMLE questions linked to Architecting Low-Code ML Solutions.
Scaling Prototypes into ML Models practice questions
Practise PMLE questions linked to Scaling Prototypes into ML Models.
Collaborating to manage data and models practice questions
Practise PMLE questions linked to Collaborating to manage data and models.
Solving business challenges with ML practice questions
Practise PMLE questions linked to Solving business challenges with ML.
PMLE fundamentals practice questions
Practise PMLE questions linked to PMLE fundamentals.
PMLE scenario practice questions
Practise PMLE questions linked to PMLE scenario.
PMLE troubleshooting practice questions
Practise PMLE questions linked to PMLE troubleshooting.
Practice this exam
Start a free PMLE practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this PMLE question test?
Serving and Scaling Models — This question tests Serving and Scaling Models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Update the endpoint to split traffic between the two model versions using the traffic split configuration. — Option C is correct because Vertex AI endpoints support a built-in traffic split configuration that allows you to gradually shift traffic between model versions deployed to the same endpoint. By updating the endpoint's traffic split percentages (e.g., from 100% old / 0% new to 0% old / 100% new over 24 hours), you can achieve a smooth, controlled rollout without changing client code or managing multiple endpoints.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More PMLE practice questions
- A travel booking company has a real-time recommendation system that suggests hotels and flights to users. The model is s…
- A global retail company uses Vertex AI Recommendations to provide product recommendations on their website. They have a…
- Your team is developing a machine learning model for real-time fraud detection. The training pipeline runs on Vertex AI…
- A healthcare organization is building a machine learning model to predict patient readmission risk. They have sensitive…
- You are an ML engineer at a global e-commerce company. Your team has developed a deep learning model for product recomme…
- A financial services company uses Vertex AI AutoML Tables to build a credit risk model. The dataset contains 500,000 row…
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.