- A
Use streaming updates to continuously update the index.
Why wrong: Streaming updates are for near-real-time changes, but the scenario describes daily batch updates.
- B
Create a new index version, deploy it to the same endpoint, and then update the endpoint to use the new index version.
Correct. This allows zero-downtime updates.
- C
Update the existing index in place by calling the index update API.
Why wrong: In-place updates are not supported; you must create a new index version.
- D
Delete the old index and create a new index each day, then deploy the new index to a new endpoint and update DNS.
Why wrong: Causes downtime during deletion and redeployment.
Question 843 of 1,000
PMLE Serving and Scaling Models Practice Question
This PMLE practice question tests your understanding of serving and scaling models. 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.
Your team has built a low-latency similarity search service using Vertex AI Matching Engine (Vector Search). The index is updated daily with new embeddings. You need to serve the latest index without downtime. What is the correct deployment strategy?
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
✓
Create a new index version, deploy it to the same endpoint, and then update the endpoint to use the new index version.
Option B is correct because Vertex AI Matching Engine supports deploying a new index version to the same endpoint without downtime. You create a new index version from the updated embeddings, deploy it to the existing endpoint, and then update the endpoint to use the new version. This allows traffic to seamlessly switch to the updated index once it is fully deployed, avoiding any service interruption.
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 streaming updates to continuously update the index.
Why it's wrong here
Streaming updates are for near-real-time changes, but the scenario describes daily batch updates.
- ✓
Create a new index version, deploy it to the same endpoint, and then update the endpoint to use the new index version.
Why this is correct
Correct. This allows zero-downtime updates.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Update the existing index in place by calling the index update API.
Why it's wrong here
In-place updates are not supported; you must create a new index version.
- ✗
Delete the old index and create a new index each day, then deploy the new index to a new endpoint and update DNS.
Why it's wrong here
Causes downtime during deletion and redeployment.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume streaming updates (Option A) are possible for low-latency similarity search, but Vertex AI Matching Engine requires batch index creation and does not support real-time streaming updates, making versioned deployment the only correct approach for zero-downtime updates.
Trap categories for this question
Scenario analysis trap
Streaming updates are for near-real-time changes, but the scenario describes daily batch updates.
Detailed technical explanation
How to think about this question
Vertex AI Matching Engine uses a distributed approximate nearest neighbor (ANN) algorithm based on ScaNN. Each index version is an immutable snapshot of the embeddings at a point in time. Deploying a new index version to the same endpoint leverages the endpoint's existing infrastructure and load balancers, allowing a smooth transition without rebuilding network paths or reconfiguring clients. The endpoint update operation is atomic, ensuring that traffic is only routed to the new index once it is fully ready.
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.
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Serving and Scaling Models — study guide chapter
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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: Create a new index version, deploy it to the same endpoint, and then update the endpoint to use the new index version. — Option B is correct because Vertex AI Matching Engine supports deploying a new index version to the same endpoint without downtime. You create a new index version from the updated embeddings, deploy it to the existing endpoint, and then update the endpoint to use the new version. This allows traffic to seamlessly switch to the updated index once it is fully deployed, avoiding any service interruption.
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.
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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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