Skip to content

Click in-app to access the full platform documentation for your version of DataRobot.

Prediction environments

Models that run on your own infrastructure (outside of DataRobot) may be run in different environments and can have differing deployment permissions and approval processes. For example, while any user may have permission to deploy a model to a test environment, deployment to production may require a strict approval workflow and only be permitted by those authorized to do so. Prediction environments support this deployment governance by grouping deployment environments and supporting grouped deployment permissions and approval workflows. You can create, manage, and share 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 MLOps Agent.

Add a prediction environment

To add a prediction environment to DataRobot, navigate to the Deployments > Prediction Environments page and select Add prediction environment.

Complete the fields:

  • Name the environment.
  • Provide a description (if desired).
  • Specify the platform from which the model is running and making predictions.
Model type support

Note that different environments may support different model types: DataRobot-built, Scoring Code, custom, or external. When an administrator creates a prediction environment, they select which model types are supported.

Once completed, click Add environment. The environment is now available from the prediction environment dashboard.

Select a prediction environment

When you have added a prediction environment to DataRobot, you can then deploy a model and use the prediction environment for the deployment. Specify the prediction environment in the Inference section.

Note that once an environment is specified and the deployment is created, the prediction environment cannot be changed.

After specifying an environment, complete the deployment creation workflow.

Sharing

The sharing capability allows appropriate user roles to grant permissions for prediction environments.

When you have created a prediction environment and want to share it with others, select Share () from the dashboard.

This takes you to the sharing window, which lists each associated user and their role. To remove a user, click the X button to the right of their role.

To re-assign a user's role, click on the assigned role and assign a new one from the dropdown.

To add a new user, enter their username in the Share with field and choose their role from the dropdown. Then click Share.

This action initiates an email notification.


Updated November 5, 2021
Back to top