---
title: Superwise
description: Model observability platform for machine learning models in production
breadcrumbs: Docs > Integrations > Superwise
---

# Superwise
Supported OS Integration version1.0.0
## Overview{% #overview %}

[Superwise](https://www.superwise.ai/) provides model observability for high-scale machine learning (ML) operations. Superwise's model observability gives you visibility and context into your models' behaviors, so you can easily monitor model risks based on different use cases. With Superwise, data scientists, ML engineers, and business ops get model observability without alert fatigue, so you can be confident about your model management.



Superwise's model metrics and incidents integration sends out-of-the-box model metrics, including drift, activity, incidents, and custom metrics, directly to Datadog. You get an overview of which models are not predicting the expected results, which can be configured to any use case, logic, segmentation, threshold, and sensitivity.

With the Datadog integration configured in Superwise, standard model metrics are sent to Datadog, and users get model observability dashboards in Datadog. You can configure any specific model metric and incident policy, and send them to Datadog for model observability that is tailored to your use case.

## Setup{% #setup %}

1. Go to [Superwise portal](https://portal.superwise.ai/) and select **Integrations**.

1. Click **Create a new channel** and select **Datadog**.



1. Input your Datadog API and application keys, and click **Test**. A test request is sent to your Datadog account to validate the integration. If the request was successfully sent, there is a message in Superwise saying the test was delivered successfully. To finish the setup, click **Create channel**.



1. When setup is complete, the new Datadog integration widget is available:

### Validation{% #validation %}

In Datadog, go to **Metrics Explorer** and search for the metric `superwise.integration.test` to verify that the integration between Superwise and Datadog is working.



## Data Collected{% #data-collected %}

### Metrics{% #metrics %}

|  |
|  |
| **superwise.metric.overall.data\_drift**(gauge)           | Average distribution shifts across all features.*Shown as day*                        |
| **superwise.metric.overall.weighted\_data\_drift**(gauge) | Average distribution shifts across all features weighted by importance.*Shown as day* |
| **superwise.metric.overall.quantity**(gauge)              | Number of records sent.*Shown as day*                                                 |

### Events{% #events %}

The Superwise integration does not include any events.

### Service Checks{% #service-checks %}

The Superwise integration does not include any service checks.

## Troubleshooting{% #troubleshooting %}

Need help? See the [Superwise documentation](https://docs.superwise.ai).

## Further Reading{% #further-reading %}

- [Monitor model performance with Superwise's offering in the Datadog Marketplace](https://www.datadoghq.com/blog/superwise-datadog-marketplace/)