- A
Store the index in Cloud Storage and query via Python
Why wrong: Direct storage query is not supported for low latency.
- B
Enable streaming updates for the index
Streaming updates allow real-time insertion without downtime.
- C
Use a brute-force index for exact results
Why wrong: Brute-force is slow for large datasets and frequent updates.
- D
Deploy the index to a Vertex AI Matching Engine endpoint
Deployed index on endpoint provides low-latency queries.
- E
Use batch updates only
Why wrong: Batch updates require rebuilding and cause downtime.
Question 239 of 1,000
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.
A company uses Vertex AI Matching Engine for real-time recommendations. They need to serve queries with low latency and support frequent updates. Which two configurations are appropriate? (Choose 2)
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
✓
Enable streaming updates for the index
Vertex AI Matching Engine supports streaming updates, which allow real-time insertion, deletion, and modification of vectors without rebuilding the entire index. This is essential for use cases requiring frequent updates, such as real-time recommendation systems, because it maintains low latency for serving queries while keeping the index current.
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.
- ✗
Store the index in Cloud Storage and query via Python
Why it's wrong here
Direct storage query is not supported for low latency.
- ✓
Enable streaming updates for the index
Why this is correct
Streaming updates allow real-time insertion without downtime.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a brute-force index for exact results
Why it's wrong here
Brute-force is slow for large datasets and frequent updates.
- ✓
Deploy the index to a Vertex AI Matching Engine endpoint
Why this is correct
Deployed index on endpoint provides low-latency queries.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use batch updates only
Why it's wrong here
Batch updates require rebuilding and cause downtime.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that in Google's Vertex AI Matching Engine, candidates often confuse batch updates with streaming updates, assuming that batch updates can be made frequent enough to approximate real-time, but they fail to recognize that batch updates require full index rebuilds, which introduce significant latency and downtime for serving.
Detailed technical explanation
How to think about this question
Matching Engine uses ScaNN (Scalable Nearest Neighbors) under the hood, which employs techniques like anisotropic quantization and tree-based partitioning to balance recall and latency. Streaming updates leverage a delta-index mechanism where incremental changes are applied to a separate mutable segment, which is periodically merged with the main index to avoid full rebuilds, ensuring query performance remains consistent even during active writes.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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
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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: Enable streaming updates for the index — Vertex AI Matching Engine supports streaming updates, which allow real-time insertion, deletion, and modification of vectors without rebuilding the entire index. This is essential for use cases requiring frequent updates, such as real-time recommendation systems, because it maintains low latency for serving queries while keeping the index current.
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 →
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Last reviewed: Jul 4, 2026
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