# Deployment settings > Deployment settings - After you create and configure a deployment, you can use the settings tabs for > individual features to add or update deployment functionality. This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context. Companion generated at `2026-04-24T16:03:56.554818+00:00` (UTC). ## Primary page - [Deployment settings](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/index.html): Full documentation for this topic (HTML). ## Related documentation - [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page. - [MLOps](https://docs.datarobot.com/en/docs/classic-ui/mlops/index.html): Linked from this page. - [create and configure a deployment](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment/deploy-methods/add-deploy-info.html): Linked from this page. - [Set up service health monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/service-health-settings.html): Linked from this page. - [segmented analysis](https://docs.datarobot.com/en/docs/classic-ui/mlops/monitor/deploy-segment.html): Linked from this page. - [Set up data drift monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/data-drift-settings.html): Linked from this page. - [data drift monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/monitor/data-drift.html): Linked from this page. - [Set up accuracy monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/accuracy-settings.html): Linked from this page. - [accuracy monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/monitor/deploy-accuracy.html): Linked from this page. - [Set up fairness monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/fairness-settings.html): Linked from this page. - [fairness monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/governance/mlops-fairness.html): Linked from this page. - [Set up humility rules](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/humility-settings.html): Linked from this page. - [humility monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/governance/humble.html): Linked from this page. - [Configure retraining](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/retraining-settings.html): Linked from this page. - [Automated Retraining](https://docs.datarobot.com/en/docs/classic-ui/mlops/manage-mlops/set-up-auto-retraining.html): Linked from this page. - [Configure challengers](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/challengers-settings.html): Linked from this page. - [challenger comparison](https://docs.datarobot.com/en/docs/api/dev-learning/python/mlops/challengers.html): Linked from this page. - [Review predictions settings](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/predictions-settings.html): Linked from this page. - [Enable data exploration](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/data-exploration-settings.html): Linked from this page. - [data exploration](https://docs.datarobot.com/en/docs/api/reference/sdk/data-exploration.html): Linked from this page. - [Set up custom metrics monitoring](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/custom-metrics-settings.html): Linked from this page. - [custom metrics](https://docs.datarobot.com/en/docs/api/reference/sdk/custom-metrics.html): Linked from this page. - [Set up timeliness tracking](https://docs.datarobot.com/en/docs/classic-ui/mlops/deployment-settings/usage-settings.html): Linked from this page. - [timeliness tracking](https://docs.datarobot.com/en/docs/classic-ui/mlops/monitor/deploy-usage.html): Linked from this page. - [prediction intervals](https://docs.datarobot.com/en/docs/classic-ui/modeling/time/ts-predictions.html#prediction-preview): Linked from this page. ## Documentation content # 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. |