Metaflow
Open SourceOpen-source framework for building, managing, scaling, and deploying real-life ML, AI, and data science projects and workflows.
Informations sur l’outil
Qu'est-ce que Metaflow ?
Metaflow is an open-source framework that enables ML/AI engineers and data scientists to develop robust Python workflows locally, scale them to the cloud with compute and data management, track experiments automatically, and deploy to production without code changes. Originally developed at Netflix and open-sourced in 2019, it is built for real-life ML, AI, and data science projects rather than just machines.
Fonctionnalités principales
Modeling with any Python libraries
Use any Python libraries for models and business logic while Metaflow manages library dependencies locally and in the cloud.
Workflow orchestration
Create robust workflows in plain Python that can be developed and debugged locally then deployed to production without changes.
Automatic versioning and experiment tracking
Metaflow tracks and stores variables inside the flow automatically for easy experiment tracking and debugging.
Cloud scaling and compute
Leverage the cloud to execute functions at scale using GPUs, multiple cores, large memory, and multiple instances in parallel.
Data access and versioning
Access data from data warehouses; Metaflow flows data across steps while versioning everything.
Production deployment
Deploy workflows to production with a single command or click and integrate with other systems through events without changing code.
Bring your own cloud
Deploy the Metaflow stack on your own cloud account or on-premise Kubernetes cluster, integrating with existing infrastructure, security, and data governance.
Local development and notebooks
Explore with notebooks, develop with Metaflow, and test and debug locally with automatic result storage and tracking.
Recursive and conditional steps
Support for recursive and conditional steps in flows.
Custom decorators and dependency management
Develop custom decorators and include any PyPI packages; support for uv and configurable Metaflow.
Checkpointing and real-time cards
Checkpointing progress and real-time dynamic cards for monitoring.
Programmatic run and deploy
Run and deploy flows programmatically with one-click local development stack and spin for quick development.
Cas d'utilisation
- #1
Real-life ML and AI project management
Build and manage production ML, AI, and data science projects including GenAI, computer vision, statistics, and operations research.
- #2
Experimentation and model development
Accelerate experimentation, test more models, and develop safely with automatic tracking and local-to-cloud workflows.
- #3
Production ML product development
Codify and orchestrate complex multi-stage workflows for reliable ML products, as used by teams like 23andMe.
- #4
Scaling data science processes
Improve data science processes, accelerate ML within media and other industries, and enable collaboration at scale.
Plans tarifaires
Open-source Metaflow makes it quick and easy to build and manage real-life ML, AI, and data science projects. Originally developed and open-sourced by Netflix in 2019.
Alternatives
Foire aux questions
What is Metaflow?
Is Metaflow free?
Who is Metaflow designed for?
What platforms and clouds does Metaflow support?
Can I use any Python libraries with Metaflow?
How does Metaflow handle experiment tracking and versioning?
Metaflow Contacts et réseaux sociaux
- SociétéNetflix
- Site Internet :
- GitHub
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