Argo Workflows

A Kubernetes-native workflow engine in which every step runs as a container, used for machine-learning pipelines, batch jobs, data processing and CI/CD.

17.1k stars, 3.7k forks Go On GitHub since August 2017

Visit website View on GitHub How to run it

What is Argo Workflows?

Argo Workflows adds workflows to Kubernetes as a custom resource. Each step is a container, and steps run in sequence or as a directed acyclic graph of dependencies, often in parallel across the cluster. Workflows are written in YAML, or in Python through the Hera SDK, and a web UI shows runs, logs and artifacts. It is a graduated project of the Cloud Native Computing Foundation.

Good fit if

  • You already run Kubernetes and want pipelines that use the cluster directly.
  • You run compute-heavy machine-learning or data jobs that scale out in parallel.
  • You want a vendor-neutral project with foundation governance.

Look elsewhere if

Before you adopt it

Argo Workflows is Apache-2.0, with no paid parts in the repository. It requires a Kubernetes cluster; GitHub releases include the command-line client for Linux, macOS and Windows.

Drafted with AI from the project's README and repository data, then checked against that data on 30 October 2026. Report a correction

Argo Workflows health: is it still maintained?

86 of 100, actively developed

  • Activity
    354 commits in the last 90 days, the latest on 30 October 2026.
    30 / 30
  • Contributors
    19 people wrote the latest 100 commits; the most active wrote 36% of them.
    17 / 20
  • Releases
    15 releases in the last 12 months; the latest, v4.1.6, on 22 October 2026.
    19 / 20
  • Replies to issues
    Maintainers answered 25% of recent issues, with a median first reply after 3 days.
    12 / 20
  • Security practices
    OpenSSF Scorecard 7.5 of 10.
    8 / 10

Read from GitHub on 1 November 2026. How the score works

Argo Workflows license: is it open source?

Argo Workflows uses Apache-2.0, an open-source license approved by the OSI.

  1. August 2017First published on GitHub.
  2. TodayApache-2.0.

How to run Argo Workflows yourself

Docker
Dockerfile or compose file in the repository
Compose file
None in the repository
Setup effort
Not rated: no compose file to judge from
Kubernetes
No Helm chart in the repository
Desktop and mobile
Builds for Linux, Windows, macOS, including ARM in GitHub releases
Interface languages
English only

Install instructions: argo-workflows.readthedocs.io or the README on GitHub.

Alternatives to Argo Workflows

  • Apache AirflowApache Airflow - A platform to programmatically author, schedule, and monitor workflows 87 health · Apache-2.0 · 47.3k stars
  • Apache DolphinSchedulerApache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow… 83 health · Apache-2.0 · 14.6k stars
  • PrefectPrefect is a workflow orchestration framework for building resilient data pipelines in Python. 80 health · Apache-2.0 · 24.1k stars
  • KestraOrchestrate everything, everywhere. The open-source control plane for workflows across data, infrastructure,… 85 health · Apache-2.0 · 30.1k stars
  • DagsterAn orchestration platform for the development, production, and observation of data assets. 68 health · Apache-2.0 · 16.4k stars

All 33 projects in Workflow automation

Questions about Argo Workflows

Is Argo Workflows open source?

Yes. Argo Workflows is published under Apache-2.0, an OSI-approved open-source license.

Is Argo Workflows still maintained?

Its health score is 86 of 100 (actively developed). It had 354 commits in the last 90 days, the latest on 30 October 2026, and its latest release came out on 22 October 2026.

How do I run Argo Workflows?

You can run it with Docker, as an app for Linux, Windows, macOS, including ARM. The README on GitHub has the exact steps.

What are the alternatives to Argo Workflows?

Close alternatives in the Workflow automation category include Apache Airflow, Apache DolphinScheduler, Prefect.