A guide to building long-term compounding knowledge infrastructure. See details on GitHub .

Flyte

A scalable, reproducible open-source workflow orchestration platform for data, ML and analytics pipelines.

Introduction

Flyte is an open-source, production-grade workflow orchestration platform focused on scalability, strong typing and reproducibility. It enables teams to build and run complex data and ML pipelines on Kubernetes.

Key features

  • Strongly typed interfaces and data guardrails (Flyte types) to improve data quality and maintainability.
  • Multi-language SDK support (Python, Java, etc.) with containerized execution to isolate dependencies.
  • Advanced capabilities such as dynamic workflows, map tasks, task-level caching and failure recovery.
  • Local sandbox, CLI tools and a visual console to ease development and debugging.

Use cases

  • Production orchestration of data and ML pipelines on cloud or on-prem Kubernetes clusters.
  • Migrating research code to reproducible, versioned production workflows with data lineage.
  • Optimizing resource utilization and recovery strategies for large-scale parallel or long-running jobs.

Technical details

  • Core components implemented in Go, with SDKs (e.g., Python’s flytekit) to simplify developer experience.
  • Deep Kubernetes integration for containerized tasks, dynamic resource scheduling and multi-tenancy.
  • Extensive docs and community support at https://docs.flyte.org/ , adopted by many large organizations.

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Flyte
Resource Info
Author Flyte Community
Added Date 2025-09-30
Open Source Since 2019-10-21
Tags
Open Source ML Platform Workflow Deployment