---
title: Custom monitoring metrics (video)
description: See the process for defining and creating custom LLMOps and MLOps monitoring metrics in DataRobot.
---

# Custom monitoring metrics (video) {: #custom-monitoring-metrics-video }

User-defined metrics supplement the out-of-the-box metrics provided by DataRobot. The standard metrics include everything available on the [Service Health](service-health){ target=_blank }, [Data Drift](data-drift){ target=_blank }, [Accuracy](deploy-accuracy){ target=_blank }, and [Fairness](mlops-fairness){ target=_blank } tabs.

In this video, you’ll learn about custom metrics for deployment monitoring, including examples in generative and predictive deployments. It covers, in code, the process for creating a custom metric in DataRobot and submitting custom metric values to a deployment. Then, you will learn how to modify the layout of the metrics and configure notifications and alerts in the DataRobot graphical user interface.


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<div style="position:relative;padding-bottom:56.25%;">
 <iframe style="width:100%;height:100%;position:absolute;left:0px;top:0px;" title="Custom Metrics for MLOps and LLMOps Monitoring" frameborder="0" width="100%" height="100%"
 allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" src="https://www.youtube.com/embed/awJ6YYE2zOU?si=zpK9XtBzON8uQHy9" allowfullscreen></iframe>
</div>
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## Read more {: #read-more }

* [Custom Metrics tab](custom-metrics){ target=_blank }
* [Using Custom Metrics to monitor GenAI](https://github.com/datarobot-community/ai-accelerators/tree/main/generative_ai/Using%20Custom%20Metrics%20to%20effectively%20monitor%20Generative%20AI){ target=_blank } (AI Accelerator)
