Overview
Metaflow abstracts infrastructure so data scientists can prototype locally and scale to the cloud with a single decorator, while maintaining versioned data and code snapshots.
Key Capabilities
- Pythonic DAG definition with automatic resume/replay
- Built-in artifact store & data versioning
- Seamless scaling to AWS Batch / Kubernetes / Argo
- Integrated notebook, CLI and UI for monitoring
- Supports R, Conda, and integrations with SageMaker & Ray
