Description
Metaflow is an open-source framework for building and managing high-performance data science projects with infrastructure-level support for AI workflows. Originally developed at Netflix and designed for production data science, the platform provides a unified API to seamlessly access compute, storage, and deployment infrastructure without requiring specialized DevOps knowledge. With its human-centric design philosophy, Metaflow enables data scientists to focus on solving business problems while transparently handling the complexity of distributed computing, versioning, and deployment, making sophisticated machine learning workflows accessible to all data practitioners.
Key Features
- Human-centric data science workflows
- Infrastructure abstraction layer
- Versioned experiment tracking
- Scalable compute orchestration
- Unified deployment interface
Use Cases
- Production machine learning pipelines
- Scalable data processing workflows
- Reproducible research projects
- Cross-functional data science collaboration
- Enterprise AI standardization
Pricing Model
Open-source with enterprise support options
Integrations
Cloud computing services, Container orchestration systems, Notebook environments, CI/CD pipelines, Model serving infrastructure
Target Audience
Data scientists, Machine learning engineers, Research scientists, ML infrastructure teams, Enterprise data science organizations
Launch Date
2019
Available On
Open-source framework, Cloud infrastructure, Hybrid computing environments
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