# Add integration


MLflow integration allows you to use MLflow with pipelines to select a tracking server or serverless application, choose an experiment, and log metrics.

## Key concepts


**Default app creation** - A default MLflow application will be created when you enter the pipeline visual editor.

**Integrations panel** - A new integrations panel includes MLflow, which you can select and configure.

**Update app and experiment** - The option to override selected application and experiment during the pipeline execution.

## How it works

+ Go to **Pipeline Visual Editor**
+ Choose **Integration** on the toolbar
+ Choose **MLflow**
+ Configure the MLflow app and experiment

## Example screenshots


Integrations side panel

![\[The to do description.\]](http://docs.amazonaws.cn/en_us/sagemaker/latest/dg/images/screenshot-pipeline-1.png)


MLflow configuration

![\[The to do description.\]](http://docs.amazonaws.cn/en_us/sagemaker/latest/dg/images/screenshot-pipeline-2.png)


How to override experiment during pipeline execution

![\[The to do description.\]](http://docs.amazonaws.cn/en_us/sagemaker/latest/dg/images/screenshot-pipeline-3.png)