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What is the point of the model staging and promotion functions in MLflow?

User16826992666
Valued Contributor

Why not just directly deploy the model where you need it in production?

1 ACCEPTED SOLUTION

Accepted Solutions

sean_owen
Databricks Employee
Databricks Employee

The Model Registry is mostly a workflow tool. It helps 'gate' the process, so that (for example) only authorized users can set a model to be the newest Production version of a model - that's not something just anyone should be able to do!

The Registry can trigger webhooks when a model enters a new state, for example to run a testing notebook when a new Staging candidate appears.

It also helps serve as a single source of truth: what's the current production model? rather than pass around the run ID "abc123456..." informally, the stage tags in the Registry let any process look up the 'latest production model' reliably.

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1 REPLY 1

sean_owen
Databricks Employee
Databricks Employee

The Model Registry is mostly a workflow tool. It helps 'gate' the process, so that (for example) only authorized users can set a model to be the newest Production version of a model - that's not something just anyone should be able to do!

The Registry can trigger webhooks when a model enters a new state, for example to run a testing notebook when a new Staging candidate appears.

It also helps serve as a single source of truth: what's the current production model? rather than pass around the run ID "abc123456..." informally, the stage tags in the Registry let any process look up the 'latest production model' reliably.

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