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On-premise users: click in-app to access the full platform documentation for your version of DataRobot.

Review and add prediction environments

On the Prediction Environments page, you can review the DataRobot prediction environments available to you and create external prediction environments for both DataRobot models running on the Portable Prediction Server and remote models monitored by the monitoring agent.

Review DataRobot prediction environments

While you can't create DataRobot prediction environments, you can still view them on the Prediction Environments tab. Review the DataRobot prediction environments available to your organization by locating the environments with DataRobot in the Platform column:

These prediction environments are created by DataRobot and cannot be configured; however, you can deploy models to these prediction environments from this page.

Availability information

If you have Real-time predictions on DataRobot serverless prediction environments enabled, you can create DataRobot prediction environments. This feature is off by default. Contact your DataRobot representative or administrator for information on enabling it.

Feature flag: Enable Real-time (Interactive) Predictions on K8s Prediction Environments, Enable Real-time GenAI Predictions on K8s Prediction Environments

Add a new external prediction environment

You can create, manage, and share external prediction environments across DataRobot. This allows you to specify the prediction environments used for both DataRobot models running on the Portable Prediction Server and remote models monitored by the monitoring agent.

To deploy models on external infrastructure, you create a custom external prediction environment:

  1. Click Deployments > Prediction Environments and then click + Add prediction environment.

  2. In the Add prediction environment dialog box, complete the following fields:

    Field Description
    Name Enter a descriptive prediction environment name.
    Description (Optional) Enter a description of the external prediction environment.
    Platform Select the external platform on which the model is running and making predictions.
  3. Under Supported Model Formats, select one or more formats to control which models can be deployed to the prediction environment, either manually or using the management agent. The available model formats are DataRobot or DataRobot Scoring Code, External Model, and Custom Model.


    You can only select one of DataRobot or DataRobot Scoring Code.

  4. (Optional) If you want to manage your external model with DataRobot MLOps, click Use Management Agent to allow the MLOps Management Agent to automate the deployment, replacement, and monitoring of models in this prediction environment.

  5. Once you configure the environment settings, click Add environment.

The environment is now available from the Prediction Environments page.

Select a prediction environment for a deployment

After you add a prediction environment to DataRobot, you can deploy a model and use the prediction environment for the deployment.

Specify the prediction environment in the Prediction History and Service Health section:


After you specify a prediction environment and create the deployment, you cannot change the prediction environment.

Updated May 16, 2024