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Question 244 - Professional Machine Learning Engineer discussion

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You recently created a new Google Cloud Project After testing that you can submit a Vertex Al Pipeline job from the Cloud Shell, you want to use a Vertex Al Workbench user-managed notebook instance to run your code from that instance You created the instance and ran the code but this time the job fails with an insufficient permissions error. What should you do?

A.
Ensure that the Workbench instance that you created is in the same region of the Vertex Al Pipelines resources you will use.
Answers
A.
Ensure that the Workbench instance that you created is in the same region of the Vertex Al Pipelines resources you will use.
B.
Ensure that the Vertex Al Workbench instance is on the same subnetwork of the Vertex Al Pipeline resources that you will use.
Answers
B.
Ensure that the Vertex Al Workbench instance is on the same subnetwork of the Vertex Al Pipeline resources that you will use.
C.
Ensure that the Vertex Al Workbench instance is assigned the Identity and Access Management (1AM) Vertex Al User rote.
Answers
C.
Ensure that the Vertex Al Workbench instance is assigned the Identity and Access Management (1AM) Vertex Al User rote.
D.
Ensure that the Vertex Al Workbench instance is assigned the Identity and Access Management (1AM) Notebooks Runner role.
Answers
D.
Ensure that the Vertex Al Workbench instance is assigned the Identity and Access Management (1AM) Notebooks Runner role.
Suggested answer: C

Explanation:

Vertex AI Workbench is an integrated development environment (IDE) that allows you to create and run Jupyter notebooks on Google Cloud. Vertex AI Pipelines is a service that allows you to create and manage machine learning workflows using Vertex AI components. To submit a Vertex AI Pipeline job from a Vertex AI Workbench instance, you need to have the appropriate permissions to access the Vertex AI resources. The Identity and Access Management (IAM) Vertex AI User role is a predefined role that grants the minimum permissions required to use Vertex AI services, such as creating and deploying models, endpoints, and pipelines. By assigning the Vertex AI User role to the Vertex AI Workbench instance, you can ensure that the instance has sufficient permissions to submit a Vertex AI Pipeline job. You can assign the role to the instance by using the Cloud Console, the gcloud command-line tool, or the Cloud IAM API.Reference: The answer can be verified from official Google Cloud documentation and resources related to Vertex AI Workbench, Vertex AI Pipelines, and IAM.

Vertex AI Workbench | Google Cloud

Vertex AI Pipelines | Google Cloud

Vertex AI roles | Google Cloud

Granting, changing, and revoking access to resources | Google Cloud

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asked 18/09/2024
Miles Greenyer
38 questions
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