You work on a growing team of more than 50 data scientists who all use AI Platform. You are designing a strategy to organize your jobs, models, and versions in a clean and scalable way. Which…

Question

Options

• ASet up restrictive IAM permissions on the AI Platform notebooks so that only a single user or
• BSeparate each data scientist's work into a different project to ensure that the jobs, models, and
• CUse labels to organize resources into descriptive categories.
• DSet up a BigQuery sink for Cloud Logging logs that is appropriately filtered to capture information

• A
  7% (2)
• B
  3% (1)
• C
  76% (22)
• D
  14% (4)

Explanation

Labels are key-value metadata tags that can be attached to AI Platform jobs, models, and versions. They provide a lightweight, flexible, and scalable way to organize resources by team, experiment, use case, environment, or any other category-without any infrastructure overhead. Creating one GCP project per data scientist (B) is extremely expensive and operationally burdensome to manage at scale. Restricting IAM on notebooks (A) controls access but does not organize resources. A BigQuery log sink (D) is useful for auditing but not for organizing resources. Labels are the GCP-native, recommended approach for resource organization at scale.

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