MLflow
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle.
FreeWebAPICLIOpen sourceKoreanMultimodal
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MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It offers four primary components: Tracking for logging experiments, Projects for packaging code, Models for managing and deploying models, and a Model Registry for centralized versioning. MLflow is designed to be library-agnostic and scalable, supporting a wide range of ML frameworks and deployment environments.
Key features
- Experiment Tracking
- Reproducible Projects
- Model Deployment
- Centralized Model Registry
- LLM Tracking & Evaluation
- REST API & CLI Support
- Library Agnostic Design
Pricing
Use cases
- Logging Training Metrics
- Model Versioning & Approval
- Model Deployment to Serving Environments
- LLM Application Evaluation
Who it is for
ML EngineersData EngineersDevOps Engineers
Integrations
DatabricksApache SparkKubernetesDockerTensorFlow
Tags
MLOps
How we verified this
Company, pricing, and feature details come from the primary sources below and our latest verification pass. When sources disagree, the official source and the most recent check win.
Last verified 08/30/2026Verified sources: 2
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