Introduction
Metaflow, originally developed at Netflix, is an open-source framework that helps data scientists and engineers manage code, data and compute from rapid prototyping in notebooks to production-grade deployments.
Key features
- Pythonic API and notebook-friendly workflows for fast prototyping.
- Built-in experiment tracking, versioning and visualization with checkpoints for large-scale parallel work.
- Easy deployment to production orchestrators and integrations with cloud storage and compute backends.
Use cases
- Develop and debug ML workflows locally, then scale to cloud clusters for production runs.
- Manage the full lifecycle of model training, data processing and deployment.
- Establish auditable experiment and model management workflows across teams.
Technical details
- Primarily Python-based with a lightweight CLI and SDK; core components are open-source and community maintained.
- Supports multi-cloud and on-prem environments, containerized execution and efficient data access for scaling.
- Comprehensive docs and an active community ( https://docs.metaflow.org/ ).