argo-workflows

What is Argo Workflows?

Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition).

• Define workflows where each step is a container.
• Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG).
• Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes.

Argo is a Cloud Native Computing Foundation (CNCF) graduated project.

Use Cases

• Machine Learning pipelines
• Data and batch processing
• Infrastructure automation
• CI/CD
• Other use cases

Why Argo Workflows?

• Argo Workflows is the most popular workflow execution engine for Kubernetes.
• Light-weight, scalable, and easier to use.
  • Including for Python users through the Hera Python SDK for Argo Workflows.
• Designed from the ground up for containers without the overhead and limitations of legacy VM and server-based environments.
• Cloud agnostic and can run on any Kubernetes cluster.

Read what people said in our latest survey

Try Argo Workflows

You can try Argo Workflows via one of the following:

1. Interactive Training Material
2. Access the demo environment

Who uses Argo Workflows?

About 200+ organizations are officially using Argo Workflows

Ecosystem

Just some of the projects that use or rely on Argo Workflows (complete list here):

• Argo Events
• Hera
• Katib
• Kedro
• Kubeflow Pipelines
• Netflix Metaflow
• Piper
• Seldon
• SQLFlow

Client Libraries

Check out our Java, Golang, Python (Hera), and Typescript (Juno) clients.

Quickstart

• Get started here
• Walk-through examples

Documentation

View the docs

Features

An incomplete list of features Argo Workflows provides:

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