Google Cloud Digital Leader 2025 – 400 Free Practice Questions to Pass the Exam

The AI Platform is the correct choice for automated deployment of machine learning models in Google Cloud Platform (GCP). This service provides a complete end-to-end platform for building, training, and deploying machine learning models. With the AI Platform, users can take advantage of its capabilities for model versioning, scalable serving, and seamless integration with other Google Cloud services.

When you deploy a model using the AI Platform, it automatically manages the underlying infrastructure, allowing you to focus on your model without worrying about resource allocation or scaling issues. It supports both online predictions for real-time usage and batch predictions for larger datasets, making it a flexible solution for various needs.

Other choices, while valuable in their respective contexts, do not specifically focus on the automated deployment of machine learning models. Google Cloud ML Engine is actually an earlier name for the same service as AI Platform, so it is not the most current answer. Google Kubernetes Engine is primarily for managing containerized applications, which includes machine learning models, but it requires additional configuration and management overhead. Cloud Functions is a serverless execution environment for event-driven computing but does not cater specifically to machine learning model deployment. Thus, the AI Platform stands out as the most comprehensive and direct option for automating model deployment in GCP