# Add external prediction environments
URL: https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/prediction-env/ext-pred-env.html

> Manage and control user access to environments on the prediction environment dashboard and specify the prediction environment for any deployment.

# Add external 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. External prediction environments support this deployment governance by grouping deployment environments and supporting grouped deployment permissions and approval workflows.

## Add an external prediction environment

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](https://docs.datarobot.com/en/docs/classic-ui/predictions/port-pred/pps/portable-pps.html) and remote models monitored by the [monitoring agent](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/mlops-agent/index.html).

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

1. ClickDeployments > Prediction Environmentsand then click+ Add prediction environment.
2. In theAdd prediction environmentdialog box, complete the following fields: FieldDescriptionNameEnter a descriptive prediction environment name.Description(Optional) Enter a description of the external prediction environment.PlatformSelect the external platform on which the model is running and making predictions.
3. UnderSupported 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 areDataRobotorDataRobot Scoring Code,External Model, andCustom Model. ImportantYou can only select one ofDataRobotorDataRobot Scoring Code.
4. (Optional) If you want to manage your external model with DataRobot MLOps, clickUse Management Agentto allow theMLOps Management Agentto automate the deployment, replacement, and monitoring of models in this prediction environment.
5. Once you configure the environment settings, clickAdd 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](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/deploy-methods/index.html) and use the prediction environment for the deployment.

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

> [!NOTE] Prediction environments for external models
> External models run outside DataRobot and must be deployed to an external prediction environment. Do not deploy external models to a DataRobot Serverless prediction environment.

> [!WARNING] Changing the prediction environment
> After you specify a prediction environment and create the deployment, you cannot change the prediction environment.

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