# Argo Workflows: A Cloud-Native Workflow Engine for Kubernetes

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Argo Workflows is an open-source, container-native workflow engine designed for orchestrating parallel jobs on Kubernetes. It allows users to define multi-step workflows where each step is a container, modeling dependencies using directed acyclic graphs (DAGs). This CNCF graduated project is ideal for machine learning pipelines, data processing, and CI/CD.

GitHub: https://github.com/argoproj/argo-workflows
OSRepos URL: https://osrepos.com/repo/argoproj-argo-workflows

## Summary

Argo Workflows is an open-source, container-native workflow engine designed for orchestrating parallel jobs on Kubernetes. It allows users to define multi-step workflows where each step is a container, modeling dependencies using directed acyclic graphs (DAGs). This CNCF graduated project is ideal for machine learning pipelines, data processing, and CI/CD.

## Topics

- argo-workflows
- kubernetes
- workflow-engine
- cloud-native
- data-processing
- machine-learning
- ci-cd
- go

## Repository Information

Last analyzed by OSRepos: Thu Feb 12 2026 00:00:24 GMT+0000 (Western European Standard Time)
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## Content

## Introduction

Argo Workflows is a powerful open-source, container-native workflow engine specifically built for orchestrating parallel jobs on Kubernetes. Implemented as a Kubernetes Custom Resource Definition (CRD), it enables users to define complex workflows where each step runs as a container. You can model multi-step processes as a sequence of tasks or capture intricate dependencies using a directed acyclic graph (DAG). As a graduated project of the Cloud Native Computing Foundation (CNCF), Argo Workflows provides a robust and scalable solution for various compute-intensive tasks.

## Installation

Getting started with Argo Workflows is straightforward. For a quick setup and to begin exploring its capabilities, refer to the official quickstart guide:

*   [Get started here](https://argo-workflows.readthedocs.io/en/latest/quick-start/){:target="_blank"}

## Examples

Argo Workflows supports a wide array of use cases, making it a versatile tool for modern cloud-native environments. You can explore practical examples and walk-throughs to understand its application across different domains:

*   **Use Cases:**
    *   [Machine Learning pipelines](https://argo-workflows.readthedocs.io/en/latest/use-cases/machine-learning/){:target="_blank"}
    *   [Data and batch processing](https://argo-workflows.readthedocs.io/en/latest/use-cases/data-processing/){:target="_blank"}
    *   [Infrastructure automation](https://argo-workflows.readthedocs.io/en/latest/use-cases/infrastructure-automation/){:target="_blank"}
    *   [CI/CD](https://argo-workflows.readthedocs.io/en/latest/use-cases/ci-cd/){:target="_blank"}
*   **Walk-through examples:**
    *   [Explore examples](https://argo-workflows.readthedocs.io/en/latest/walk-through/){:target="_blank"}

## Why Use Argo Workflows?

Argo Workflows stands out as the most popular workflow execution engine for Kubernetes due to several key advantages:

*   **Light-weight, scalable, and easy to use:** It offers a streamlined experience, including support for Python users through the [Hera Python SDK for Argo Workflows](https://hera.readthedocs.io/en/stable/){:target="_blank"}.
*   **Container-native design:** Built from the ground up for containers, it avoids the overhead and limitations of legacy VM and server-based environments.
*   **Cloud agnostic:** It can run on any Kubernetes cluster, providing flexibility across different cloud providers or on-premises setups.

## Links

*   **GitHub Repository:** [https://github.com/argoproj/argo-workflows](https://github.com/argoproj/argo-workflows){:target="_blank"}
*   **Official Website:** [https://argoproj.github.io/](https://argoproj.github.io/){:target="_blank"}
*   **Documentation:** [https://argo-workflows.readthedocs.io/en/latest/](https://argo-workflows.readthedocs.io/en/latest/){:target="_blank"}
*   **Join the Community on Slack:** [https://argoproj.github.io/community/join-slack](https://argoproj.github.io/community/join-slack){:target="_blank"}