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argoproj/argo-workflows

Container-native workflow engine for orchestrating parallel jobs on Kubernetes, implemented as a CRD.

Open-source alternative to:Apache Airflow

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What is it?

Argo Workflows runs multi-step jobs on Kubernetes, where each step is a container. Workflows can be declared as an ordered sequence of tasks or as a directed acyclic graph (DAG) that captures dependencies between tasks. It is implemented as a Kubernetes Custom Resource Definition, so workflows are managed with standard cluster tooling.

It targets compute-heavy batch work such as machine learning pipelines, data processing, infrastructure automation, and CI/CD. Steps support parameters and artifacts passed between them, conditionals, loops, retries, timeouts, and scheduled runs via cron. A web UI visualizes and manages workflows, and REST and gRPC APIs are available, along with Java, Go, Python (Hera), and TypeScript (Juno) SDKs.

The project is a CNCF graduated project and works on any Kubernetes cluster. Artifacts can be stored in S3, GCS, Azure Blob Storage, Git, HTTP endpoints and other backends.

Key features

  • 01Define workflows as DAGs or step sequences, with each step running in a container
  • 02Web UI for visualizing and managing workflows
  • 03Artifact passing to S3, GCS, Azure Blob, Git and other storage backends
  • 04Cron-based scheduled workflows and webhook triggering
  • 05REST and gRPC API plus Java, Go, Python and TypeScript SDKs
  • 06Retries, timeouts, conditionals, loops and suspend/resume at step or workflow level

Use cases

  • Running machine learning training and data processing pipelines on Kubernetes clusters
  • Orchestrating CI/CD jobs as containerized workflows
  • Automating infrastructure tasks with multi-step dependencies
  • Executing large batches of parallel compute jobs

Quick start

  1. 1

    Open the official quick-start guide in the Argo Workflows documentation

  2. 2

    Work through the walk-through examples in the documentation

Things to know

  • Requires a Kubernetes cluster, since it is implemented as a Kubernetes CRD.

In collections

Microservice frameworks & service infrastructure

Topics

#workflow#kubernetes#dag#batch-processing#pipelines#cloud-native#data-engineering#machine-learning#airflow#argo

FAQ

What is argo-workflows?
Container-native workflow engine for orchestrating parallel jobs on Kubernetes, implemented as a CRD. Argo Workflows runs multi-step jobs on Kubernetes, where each step is a container. Workflows can be declared as an ordered sequence of tasks or as a directed acyclic graph (DAG) that captures dependencies between tasks. It is implemented as a Kubernetes Custom Resource Definition, so workflows are managed with standard cluster tooling.
Is argo-workflows free to use? What license does it have?
argo-workflows is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is argo-workflows still maintained?
Actively maintained. The last commit to argo-workflows was on Nov 6, 2026.
What can I use argo-workflows for?
Running machine learning training and data processing pipelines on Kubernetes clusters Orchestrating CI/CD jobs as containerized workflows Automating infrastructure tasks with multi-step dependencies Executing large batches of parallel compute jobs
How do I install argo-workflows?
Open the official quick-start guide in the Argo Workflows documentation Work through the walk-through examples in the documentation
Where can I get argo-workflows?
The source code and installation instructions are on GitHub: https://github.com/argoproj/argo-workflows

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