You first register your model using model registry and you can deploy to MLFLow Model Serving or external services like SageMake and AzureML

The following resources provide more detail on this:

1. Databricks model registry example notebook: https://docs.databricks.com/_static/notebooks/mlflow/mlflow-model-registry-example.html
2. Databricks model lifecycle - https://docs.databricks.com/applications/machine-learning/manage-model-lifecycle/index.html
3. Databricks model registry enterprise features - https://databricks.com/blog/2020/04/15/databricks-extends-mlflow-model-registry-with-enterprise-feat...