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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 machine learning experiments and deploy the best-performing models. Managed MLflow is available in the following Nebius AI Cloud regions:
  • eu-north1: Finland
  • me-west1: Israel
  • us-central1: Kansas City, Missouri, US
  • uk-south1: United Kingdom
  • eu-west2: France (private region)

Getting started

Create your first cluster and run an experiment in it

Creating clusters

Create Managed MLflow clusters via Nebius AI Cloud interfaces

Monitoring a Managed MLflow cluster state

Control resource usage and monitor your cluster health