AI / ML ML Pipeline mature
MLflow
Open-source AI platform for agents, LLMs & ML models
20.0K stars
800 contributors
Since 2018
Comprehensive ML lifecycle platform for experiment tracking, model registry, deployment, LLM observability, prompt management, and AI Gateway with 100+ integrations.
License
Apache-2.0
Min RAM
1 GB
Min CPUs
1 core
Scaling
horizontal
Complexity
intermediate
Performance
enterprise grade
Self-hostable
✓
K8s native
✓
Offline
✕
Pricing
fully free
Docs quality
excellent
Vendor lock-in
none
Use cases
- ✓ Track and compare ML experiments across teams
- ✓ Version and deploy models to production
- ✓ Monitor LLM applications with tracing
- ✓ Manage AI Gateway for multi-provider LLM access
- ✓ Evaluate and optimize prompts systematically
Anti-patterns / when NOT to use
- ✕ Not a training framework itself
- ✕ Self-hosted tracking server needs PostgreSQL setup
- ✕ UI can be slow with very large experiment counts
Integrates with
Complements
Replaces / alternatives to
Technical specs
Language
PythonJavaR
API type
RESTSDK
Protocols
HTTP
Deployment
pipdocker
SDKs
pythonjavarjavascript
Community
GitHub stars 20.0K
Contributors 800
Commit frequency daily
Plugin ecosystem large
Backing Linux Foundation / Databricks
Funding foundation
Release
Latest version
— Last release —
Since 2018
Best fit
Team size
solosmallmediumenterprise
Industries
generalfintechhealthcaree-commerceresearch