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metaflow.org

Open-source framework for building and managing ML, AI, and data science projects.

Source rating 5.0 (79) 19k views 19k/mo traffic 0 saves Unknown
Data Real Tools(315)
More categories (10)
Data Science DEVELOPER TOOLS ML framework AI-framework Workflow orchestration Versioning Cloud computing Python Deployment Experiment Tracking
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Verdict

A quick read before you dig into the full page.

Best if
You are mL/AI engineers and need: Developing safe and reliable ML products
Pick this when
Open-source framework for building and managing ML, AI, and data science projects

Overview

Metaflow is an open-source framework originally developed at Netflix for building and managing real-life ML, AI, and data science projects. It allows data scientists and ML/AI engineers to develop, debug, and deploy workflows in plain Python, leveraging cloud resources for scalable compute and data access. Metaflow integrates seamlessly with existing infrastructure, security, and data governance policies, supporting deployment on AWS, Azure, Google Cloud, and Kubernetes.

metaflow.org screenshot

Best for

Short scenarios where metaflow.org tends to shine.

  • Developing safe and reliable ML products

    Best for ML/AI engineers

  • Accelerating ML experimentation

    Best for Data scientists

  • Improving data science processes

    Best for Data engineers

  • Powering diverse projects from GenAI to business-oriented data science

    Best for ML/AI engineers

Example outputs 1

Sample generations and before/after results for metaflow.org.

metaflow.org screenshot
metaflow.org screenshot

Access & connections

Where you can use metaflow.org, and what it plugs into.

Platforms

Web

Integrations

Kubernetes

Capabilities

What this tool accepts, produces, and is strongest at.

Highlights

  • Orchestration of data science workflows
  • Versioning of data and variables
  • Scalable compute using cloud resources
  • Seamless deployment to production
  • Integration with existing infrastructure

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Tools that often show up alongside metaflow.org in collections and comparisons.

FAQ 6

What is Metaflow?
Metaflow is an open-source framework originally developed at Netflix for building and managing real-life ML, AI, and data science projects. It allows data scientists and ML/AI engineers to develop, debug, and deploy workflows in plain Python, leveraging cloud resources for scalable compute and data access. Metaflow integrates seamlessly with existing infrastructure, security, and data governance policies, supporting deployment on AWS, Azure, Google Cloud, and Kubernetes.
How to use Metaflow?
Develop workflows in Python, debug locally, and deploy to production with a single command. Metaflow handles versioning, orchestration, and compute scaling automatically. You can also try Metaflow Sandbox in the browser for a quick taste.
What is Metaflow?
Metaflow is a human-centric framework for data science and ML/AI engineering that makes it quick and easy to build and manage real-life ML, AI, and data science projects.
Where can I deploy Metaflow?
Metaflow can be deployed on AWS (EKS and S3, or AWS Batch & AWS Step Functions), Azure (AKS and Azure Blob Storage), Google Cloud (GKE and Google Cloud Storage), and custom Kubernetes clusters.
What kind of companies use Metaflow?
Metaflow is used by hundreds of companies across industries, powering diverse projects from state-of-the-art GenAI and compute vision to business-oriented data science, statistics, and operations research.
Can I try Metaflow without deploying it?
Yes, you can try Metaflow Sandbox in the browser to get a taste of Metaflow in the cloud.
metaflow.org
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