Serve models with Databricks

In this section, you learn how to use Mosaic AI Model Serving to serve machine learning models through REST endpoints, as well as how to use MLflow for batch and streaming inference.

Mosaic AI Model Serving

Mosaic AI Model Serving provides a unified interface to deploy, govern, and query AI models. Each model you serve is available as a REST API that you can integrate into your web or client application.

Batch inference

Databricks recommends that you use MLflow to deploy MLflow models for offline (batch and streaming) inference. For more information, see Deploy models for batch inference and prediction.