AI / ML ML Pipeline stable
Metaflow
Human-friendly ML lifecycle framework from Netflix
8.0K stars
150 contributors
Since 2019
ML/AI project framework focusing on developer experience with automatic versioning, cloud scaling, notebook integration, and production deployment capabilities.
License
Apache-2.0
Min RAM
512 MB
Min CPUs
1 core
Scaling
single_node
Complexity
intermediate
Performance
medium
Self-hostable
✓
K8s native
✕
Offline
✕
Pricing
fully free
Docs quality
excellent
Vendor lock-in
none
Use cases
- ✓ Structure ML projects with reproducible steps
- ✓ Scale experiments to cloud with @batch decorator
- ✓ Version datasets and models automatically
- ✓ Transition notebook experiments to production
Anti-patterns / when NOT to use
- ✕ AWS-centric cloud integration
- ✕ Less community than MLflow
- ✕ No built-in model registry
- ✕ Not a full MLOps platform
Integrates with
Complements
Compare with alternatives
Replaces / alternatives to
Technical specs
Language
Python
API type
SDK
Protocols
HTTP
Deployment
pip
SDKs
python
Community
GitHub stars 8.0K
Contributors 150
Commit frequency weekly
Plugin ecosystem none
Backing Netflix / Outerbounds
Funding vc_backed
Release
Latest version
— Last release —
Since 2019
Best fit
Team size
solosmallmedium
Industries
generalmediae-commerceresearch