Practical Machine Learning on Databricks by Debu Sinha

Author:Debu Sinha
Language: eng
Format: epub
Publisher: Packt Publishing Pvt. Ltd.
Published: 2023-10-28T00:00:00+00:00

The following figure summarizes the workflow involving registering a model to the MLflow Model Registry, and how you can utilize MLflow webhooks to kick off Slack notifications and Databricks jobs to apply tags/comments or automate tests on the newly deployed model:

Figure 6.16 – A typical workflow for model management using webhooks

Note

Courtesy of Databricks

Once a model stage transition request is filed, the HTTP webhook can be used to notify the user/group of users who can review the request and approve it.

You can also set webhooks for a specific model or for all the models that are registered in a particular registry.

You can read about the various supported webhook events at https://docs.databricks.com/en/mlflow/model-registry-webhooks.html#webhook-events.

In the code example provided with this chapter, we are specifically using the following two events:

MODEL_VERSION_CREATED: A new model version was created for the associated model

TRANSITION_REQUEST_CREATED: A user requested a model version’s stage to be transitioned

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.