Google Professional Machine Learning Engineer Question 393
Single answerGoogle Cloud PlatformYou are designing a machine learning pipeline for a large-scale image classification project. The pipeline involves data preprocessing, model training, hyperparameter tuning, and model deployment. You want to use Google Cloud services to orchestrate and automate this workflow. Which orchestration framework would be the most suitable for managing this pipeline while ensuring integration with other Google Cloud services?
- A
Kubeflow Pipelines
- B
Apache Airflow
- C
Vertex AI Pipelines
- D
Cloud Composer
Show answer and explanation
Correct answer: C
Explanation
Vertex AI Pipelines is the optimal choice for managing ML pipelines on Google Cloud because it offers native integration with other Google Cloud services, managed infrastructure, MLOps capabilities, and ML-specific features. While other options like Kubeflow Pipelines and Cloud Composer have their merits, Vertex AI Pipelines provides the most seamless and efficient solution for the described scenario.
- A. Incorrect.
Kubeflow Pipelines is a good choice for ML workflows, but Vertex AI Pipelines is specifically built for seamless integration with Google Cloud services, offering additional features such as managed infrastructure and built-in artifact tracking.
- B. Incorrect.
Apache Airflow is a general-purpose orchestration tool that can manage workflows, but it lacks native ML-specific features and tight integration with Google Cloud's ML ecosystem.
- C. Correct.
Vertex AI Pipelines is the most suitable option for this scenario because it is designed for ML workflows and integrates deeply with other Google Cloud services like BigQuery, AI models, and managed infrastructure. It also provides end-to-end MLOps capabilities.
- D. Incorrect.
Cloud Composer is based on Apache Airflow and is better suited for general-purpose workflow orchestration rather than ML-specific pipelines. It does not provide the level of ML-specific integration and automation as Vertex AI Pipelines.