- A
Change min replicas to 0 and max replicas to 10.
This enables scale-to-zero, allowing endpoint to scale down to zero when idle.
- B
Use a custom metric to trigger scaling down to zero.
Why wrong: Vertex AI autoscaling does not support custom metrics for scaling to zero; it requires min replicas=0.
- C
Delete the endpoint when not in use and recreate it on demand.
Why wrong: This is impractical for automated serving and increases latency.
- D
Set max replicas to 0.
Why wrong: Max replicas must be at least min replicas; setting to 0 would invalidate the configuration.
Question 925 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.
You have a Vertex AI endpoint serving a model with min replicas=2 and max replicas=10. You notice that during low traffic hours, the endpoint still runs 2 replicas, incurring costs. You want to reduce costs to zero when there is no traffic. 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
✓
Change min replicas to 0 and max replicas to 10.
Setting min replicas to 0 allows Vertex AI to scale down to zero instances when there is no traffic, eliminating costs during idle periods. The endpoint will automatically scale up from 0 to handle incoming requests, while max replicas=10 ensures it can handle peak load. This is the standard approach for cost optimization in Vertex AI 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.
- ✓
Change min replicas to 0 and max replicas to 10.
Why this is correct
This enables scale-to-zero, allowing endpoint to scale down to zero when idle.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a custom metric to trigger scaling down to zero.
Why it's wrong here
Vertex AI autoscaling does not support custom metrics for scaling to zero; it requires min replicas=0.
- ✗
Delete the endpoint when not in use and recreate it on demand.
Why it's wrong here
This is impractical for automated serving and increases latency.
- ✗
Set max replicas to 0.
Why it's wrong here
Max replicas must be at least min replicas; setting to 0 would invalidate the configuration.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume min replicas must be at least 1 for the endpoint to be available, but Vertex AI supports scale-to-zero with min replicas=0, which is the correct way to eliminate idle costs.
Detailed technical explanation
How to think about this question
Vertex AI endpoints use autoscaling based on CPU utilization or request latency, but the min_replica_count parameter acts as a hard floor—the endpoint will always maintain at least that many replicas, even if idle. Setting min_replicas=0 enables true scale-to-zero, where the endpoint can be completely shut down when no requests are received, and the autoscaler will provision a new replica on the first request (cold start). This is particularly useful for development, testing, or batch inference workloads where constant availability is not required.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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: Change min replicas to 0 and max replicas to 10. — Setting min replicas to 0 allows Vertex AI to scale down to zero instances when there is no traffic, eliminating costs during idle periods. The endpoint will automatically scale up from 0 to handle incoming requests, while max replicas=10 ensures it can handle peak load. This is the standard approach for cost optimization in Vertex AI 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
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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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