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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #298

You are tasked with building an MLOps pipeline to retrain tree-based models in production. The pipeline will include components related to data ingestion, data processing, model training, model evalua

The correct answer is B. Set up a Vertex AI Pipelines to orchestrate the MLOps pipeline. Use the predefined Dataproc. This approach minimizes infrastructure management effort by leveraging Vertex AI Pipelines, a managed service designed for orchestrating machine learning workflows, which simplifies pipeline management. By using the predefined Dataproc component, you can easily integrate PySpark-

Submitted by kwame.gh· Apr 18, 2026ML pipeline operationalization

Question

You are tasked with building an MLOps pipeline to retrain tree-based models in production. The pipeline will include components related to data ingestion, data processing, model training, model evaluation, and model deployment. Your organization primarily uses PySpark-based workloads for data preprocessing. You want to minimize infrastructure management effort. How should you set up the pipeline?

Options

  • ASet up a TensorFlow Extended (TFX) pipeline on Vertex AI Pipelines to orchestrate the MLOps
  • BSet up a Vertex AI Pipelines to orchestrate the MLOps pipeline. Use the predefined Dataproc
  • CSet up Kubeflow Pipelines on Google Kubernetes Engine to orchestrate the MLOps pipeline. Write
  • DSet up Cloud Composer to orchestrate the MLOps pipeline. Use Dataproc workflow templates for

How the community answered

(34 responses)
  • A
    12% (4)
  • B
    62% (21)
  • C
    6% (2)
  • D
    21% (7)

Explanation

This approach minimizes infrastructure management effort by leveraging Vertex AI Pipelines, a managed service designed for orchestrating machine learning workflows, which simplifies pipeline management. By using the predefined Dataproc component, you can easily integrate PySpark-based workloads running on Dataproc without the need to write custom components. This setup provides a scalable and efficient solution for orchestrating the entire MLOps pipeline, from data ingestion to deployment, with minimal manual intervention for infrastructure

Topics

#MLOps pipelines#Vertex AI Pipelines#Dataproc#Pipeline orchestration

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