Flyte

The open-source, structured development platform for complex AI and data products.

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Overview

Flyte is an open-source workflow orchestration platform designed for machine learning and data processing workloads. It was originally developed at Lyft to handle production-grade ML pipelines at scale. Flyte provides a structured and reproducible way to build, deploy, and monitor complex workflows.

✨ Key Features

  • Kubernetes-native architecture
  • Strongly typed data passing
  • Workflow versioning and reproducibility
  • Caching and memoization
  • Scalable and multi-tenant

🎯 Key Differentiators

  • Kubernetes-native and highly scalable
  • Focus on reproducibility and versioning for ML
  • Strongly typed interface for data

Unique Value: Provides a structured, scalable, and reproducible platform for orchestrating complex machine learning and data pipelines, enabling teams to build production-ready AI products.

🎯 Use Cases (4)

Machine learning pipelines Large-scale data processing Bioinformatics workflows Reproducible research

✅ Best For

  • Building and managing production-grade machine learning pipelines
  • Orchestrating complex, distributed data processing jobs

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Simple, non-ML data pipelines that do not require the structure and overhead of Flyte.

🏆 Alternatives

Kubeflow Pipelines Argo Workflows Apache Airflow Metaflow

Offers a more structured and ML-centric approach than general-purpose orchestrators like Airflow, and is more language-agnostic than Metaflow.

💻 Platforms

Web API

🔌 Integrations

Kubernetes Spark Dask Ray TensorFlow PyTorch dbt

🛟 Support Options

  • ✓ Email Support
  • ✓ Live Chat
  • ✓ Dedicated Support (Union AI tier)

💰 Pricing

Contact for pricing
Free Tier Available

Free tier: Open source, self-hosted.

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