Another word from a Databricks employee:

"""

You can use the custom model approach but configuring it is painful. Plus you have ended every loggable model in the custom model. Another less intrusive solution would be to have a proxy server do the logging and then defer to MLflow model server. See very basic POC: https://github.com/amesar/mlflow-model-monitoring

Also check out Seldon Alibi for advanced monitoring.

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