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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #316

Your company recently migrated several of is ML models to Google Cloud. You have started developing models in Vertex AI. You need to implement a system that tracks model artifacts and model lineage. Y

The correct answer is A. Use a combination of Vertex AI Pipelines and the Vertex AI SDK to integrate metadata tracking. Using Vertex AI Pipelines with the Vertex AI SDK enables automatic tracking of model artifacts and lineage as part of the ML workflow. This approach integrates directly with the Vertex AI ecosystem, making it easy to reuse across different models and projects without introducing

Submitted by haruto_sh· Apr 18, 2026ML pipeline operationalization

Question

Your company recently migrated several of is ML models to Google Cloud. You have started developing models in Vertex AI. You need to implement a system that tracks model artifacts and model lineage. You want to create a simple, effective solution that can also be reused for future models. What should you do?

Options

  • AUse a combination of Vertex AI Pipelines and the Vertex AI SDK to integrate metadata tracking
  • BUse Vertex AI Pipelines for model artifacts and MLflow for model lineage.
  • CUse Vertex AI Experiments for model artifacts and use Vertex ML Metadata for model lineage.
  • DImplement a scheduled metadata tracking solution using Cloud Composer and Cloud Run

How the community answered

(29 responses)
  • A
    83% (24)
  • B
    7% (2)
  • C
    7% (2)
  • D
    3% (1)

Explanation

Using Vertex AI Pipelines with the Vertex AI SDK enables automatic tracking of model artifacts and lineage as part of the ML workflow. This approach integrates directly with the Vertex AI ecosystem, making it easy to reuse across different models and projects without introducing unnecessary complexity.

Topics

#Vertex AI Pipelines#Model Lineage#Artifact Management#Metadata Tracking

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