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Question 188 - Professional Machine Learning Engineer discussion

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You have built a custom model that performs several memory-intensive preprocessing tasks before it makes a prediction. You deployed the model to a Vertex Al endpoint. and validated that results were received in a reasonable amount of time After routing user traffic to the endpoint, you discover that the endpoint does not autoscale as expected when receiving multiple requests What should you do?

A.
Use a machine type with more memory
Answers
A.
Use a machine type with more memory
B.
Decrease the number of workers per machine
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B.
Decrease the number of workers per machine
C.
Increase the CPU utilization target in the autoscaling configurations
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C.
Increase the CPU utilization target in the autoscaling configurations
D.
Decrease the CPU utilization target in the autoscaling configurations
Answers
D.
Decrease the CPU utilization target in the autoscaling configurations
Suggested answer: D

Explanation:

According to the web search results, Vertex AI is a unified platform for machine learning development and deployment.Vertex AI offers various services and tools for building, managing, and serving machine learning models1.Vertex AI allows you to deploy your models to endpoints for online prediction, and configure the compute resources and autoscaling options for your deployed models2. Autoscaling with Vertex AI endpoints is (by default) based on the CPU utilization across all cores of the machine type you have specified. The default threshold of 60% represents 60% on all cores.For example, for a 4 core machine, that means you need 240% utilization to trigger autoscaling3. Therefore, if you discover that the endpoint does not autoscale as expected when receiving multiple requests, you might need to decrease the CPU utilization target in the autoscaling configurations. This way, you can lower the threshold for triggering autoscaling and allocate more resources to handle the prediction requests. Therefore, option D is the best way to solve the problem for the given use case. The other options are not relevant or optimal for this scenario.Reference:

Vertex AI

Deploy a model to an endpoint

Vertex AI endpoint doesn't scale up / down

Google Professional Machine Learning Certification Exam 2023

Latest Google Professional Machine Learning Engineer Actual Free Exam Questions

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asked 18/09/2024
RANA MANSOUR
33 questions
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