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Add deployment information

Regardless of where you create a new deployment (the Leaderboard, the Model Registry, or the deployment inventory) or the type of artifact (DataRobot model, custom inference model, or remote mode), you are directed to the deployment information page where you can customize the deployment.

The deployment information page outlines the capabilities of your current deployment based on the data provided, for example, training data, prediction data, or actuals. It populates fields for you to provide details about the training data, inference data, model, and your outcome data.

The progress bar at the top of the screen displays which deployment capabilities are enabled based on the data (and details about that data) you provide.

To complete the deployment:

  1. Complete the fields under the Inference header.

  2. DataRobot recommends that you upload training data (if available) to your deployment to enable more capabilities. To do so, click Add training data under the Learning header.

  3. After you add the available data and your model is fully defined, click Create deployment at the top of the screen.


    If the Create deployment button is inactive, be sure to either specify an association ID (required for enabling accuracy monitoring) or toggle off Require association ID in prediction requests.

  4. In the Review Deployment Importance window that displays, select the level of importance for your deployment (for tracking deployments that are most critical to your organization): Low, Moderate, High, or Critical.

  5. Click Create deployment. A message displays indicating that the deployment is being created. After the deployment is created, the Overview tab displays.

  6. Click the arrow to the left of the deployment name to return to the deployment inventory.

Updated September 7, 2022
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