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MLflow is a highly available platform for managing a lifecycle of machine learning experiments. You can track them, organize models into detailed versions, compare metrics and deploy customized models. Managed MLflow in Nebius AI Cloud enables you to access model artifacts, training results and tuned hyperparameters in a single interface. As a result, you can reproduce ML experiments and deploy the best performing models. The service is available in all Nebius AI Cloud regions except eu-north2 and eu-west1.

Getting started

Create your first cluster and run an experiment in it

Creating and modifying clusters

Create Managed MLflow clusters via Nebius AI Cloud interfaces

Monitoring a Managed MLflow cluster state

Control resource usage and monitor your cluster health