Mlflow supportΒΆ

If you use MLflow and kedro-mlflow for the Kedro pipeline runs monitoring, the plugin will automatically enable support for:

  • starting the experiment when the pipeline starts,

  • logging all the parameters, tags, metrics and artifacts under unified MLFlow run.

To make sure that the plugin discovery mechanism works, add kedro-mlflow as a dependencies to src/requirements.in and run:

$ pip-compile src/requirements.in > src/requirements.txt 
$ kedro install
$ kedro mlflow init

Then, adjust the kedro-mlflow configuration and point to the mlflow server by editing conf/local/mlflow.yml and adjusting mlflow_tracking_uri key. Then, build the image:

$ kedro docker build

And re-push the image to the remote registry.