MLflow

MLflow is an open-source platform designed to manage the end-to-end machine learning lifecycle. It was created by Databricks and first released in June 2018. The project is hosted under the Linux Foundation's AI & Data umbrella and has grown into one of the most widely adopted open-source ML lifecycle tools available.

MLflow provides four core components: Tracking, for logging experiments and comparing parameters and metrics; Projects, for packaging reproducible ML code; Models, for packaging and deploying models across serving environments; and Model Registry, for managing model versioning and stage transitions. The platform supports frameworks including TensorFlow, PyTorch, scikit-learn, and XGBoost. More recently, MLflow has expanded to support LLM evaluation, tracing for AI agents, and prompt management. It is used by data science and ML engineering teams across industries ranging from finance to healthcare.

MLflow is an open-source project and does not operate as an independent commercial entity with its own funding or headcount. Databricks, its primary corporate sponsor, raised $500 million at a $43 billion valuation in 2023. The MLflow GitHub repository has accumulated over 18,000 stars and contributions from hundreds of external contributors, reflecting broad community adoption beyond Databricks itself.