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Metaflow project preview
Developer ToolsAlternative to AWS Step FunctionsAlternative to SageMaker PipelinesAlternative to Kubeflow

Metaflow

Human-friendly Python/R framework for building and managing data science and ML workflows.

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LicenseApache-2.0
GitHub stars8.5k
Last commit1 weeks ago
Tags5 topics
Artifact VersioningDeveloper ToolsMl Workflow FrameworkCloud Dag OrchestrationNetflix Metaflow
Overview

Why consider Metaflow?

Metaflow is an open-source workflow framework developed by Netflix and Outerbounds. Metaflow structures data science and machine learning pipelines into directed acyclic graphs (DAGs), handling cloud orchestration, artifact versioning, and compute resource allocation on AWS and Kubernetes.

Guided learning

Learn Metaflow by building

Practical setup notes, real use cases, and copy-ready examples in one focused guide.

1 min read 2 sections
In this guide2 sections

Overview of Metaflow

Metaflow scales ML pipelines from local prototyping to cloud clusters with zero code refactoring.

Quickstart

bash
1pip install metaflow
2python flow.py run

Metaflow is licensed under the Apache License Version 2.0.

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Metaflow FAQs

Metaflow is listed as a Developer Tools tool on TiloBox. Review the overview, features, and official documentation on this page to decide whether it solves your specific workflow.

Start with the project's GitHub repository and official website for supported installation and deployment instructions. Test the setup with representative data or a small project before rolling it out more widely.

Metaflow is listed under the Apache-2.0 license. Read the complete license text and the project's notices before using, modifying, or distributing the software.

Production readiness depends on your requirements. Review maintenance activity, security practices, documentation, backup and upgrade procedures, and compatibility with your stack; then validate it in a non-production environment.

Metaflow is listed as an alternative to AWS Step Functions. Compare the core workflow, deployment model, integrations, and licensing against your must-have requirements before switching.