# Deployment settings
URL: https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/index.html

> After you create and configure a deployment, you can use the settings tabs for individual features to add or update deployment functionality.

# Deployment settings

After you [create and configure a deployment](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/deploy-methods/add-deploy-info.html), you can use the settings tabs for individual features to add or update deployment functionality:

| Topic | Describes |
| --- | --- |
| Set up service health monitoring | Enable segmented analysis to assess service health, data drift, and accuracy statistics by filtering them into unique segment attributes and values. |
| Set up data drift monitoring | Enable data drift monitoring on a deployment's Data Drift Settings tab. |
| Set up accuracy monitoring | Enable accuracy monitoring on a deployment's Accuracy Settings tab. |
| Set up fairness monitoring | Enable fairness monitoring on a deployment's Fairness Settings tab. |
| Set up humility rules | Enable humility monitoring by creating rules which enable models to recognize, in real-time, when they make uncertain predictions or receive data they have not seen before. |
| Configure retraining | Enable Automated Retraining for a deployment by defining the general retraining settings and then creating retraining policies. |
| Configure challengers | Enable challenger comparison by configuring a deployment to store prediction request data at the row level and replay predictions on a schedule. |
| Review predictions settings | Review the Predictions Settings tab to view details about your deployment's inference data. |
| Enable data exploration | Enable data exploration to export deployment data, allowing you to compute and monitor custom business or performance metrics. |
| Set up custom metrics monitoring | Enable custom metrics monitoring by defining the "at risk" and "failing" thresholds for the custom metrics you created. |
| Set up timeliness tracking | Enable timeliness tracking on a deployment's Usage Settings tab to reveal when deployment status indicators are based on old data. |
| Set prediction intervals for time series deployments | Enable prediction intervals in the prediction response for deployed time series models. |

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