MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. The Docker image of MLflow is available with the 2.4.0 tag.

After the node where you'd like to run MLflow is registered, you can set it up by following the steps of deployments as documented here.

Once the deployment is successful, MLflow is ready to use at http://localhost:5001/ by default, as seen below.

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