Configure MLFlow
With the MLFlow integration you can deploy models and explainers to Deeploy that are available in your own MLFlow model registry. You can make use of MLFlow's model stages or deploy specific model versions.
Configure MLFlow
The MLFlow integration is controlled on team level. Admins can set up the integration on the Integrations page, which is part of the Admin panel. Click Configure on the MLFlow card and Add credentials to set up the integration.
- Pre-requisites In order for Deeploy to communicate with your MLFlow tracking server there are a few requirements:
- Deeploy needs to be able to reach the server, for Deeploy private cloud this means available in the same VPC and for Deeploy cloud it needs to be publicly accessible
- Authentication needs to be enabled, which can be enforced by starting the tracking server with the
--app-name basic-authargument attached. - MLFlow version >=2.5.0
Best practices Give Deeploy the least access possible when connecting to your MLFlow server. In practice, this means having or creating a read-only user.
Workspace permissions Define which Workspaces should have access to your MLFlow credentials. You can assign your MLFlow credentials to multiple Workspaces, but each Workspace can only have one MLFlow credentials assigned to it.
Update MLFlow credentials
To update your MLFlow credentials, click on the Actions button in your MLFlow credentials table, then click Update. Updating your credentials always requires you to fill in your password.
Changing Workspace permissions
To change the Workspaces to which the MLFlow credentials are assigned to, click on the Actions button in your MLFlow credentials table, then click Manage permissions. Now select or deselect the Workspaces you want to change, and click Save.
Delete MLFlow credentials
To delete your MLFlow credentials, click on the Actions button in your MLFlow credentials table, then click Delete. Click Delete in the dialog to confirm the deletion of your credentials.