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https://github.com/argoproj/argo
Workflow Engine for Kubernetes
https://github.com/argoproj/argo
airflow argo argo-workflows batch-processing cloud-native cncf dag data-engineering gitops hacktoberfest k8s knative kubernetes machine-learning mlops pipelines workflow workflow-engine
Last synced: 3 months ago
JSON representation
Workflow Engine for Kubernetes
- Host: GitHub
- URL: https://github.com/argoproj/argo
- Owner: argoproj
- License: apache-2.0
- Created: 2017-08-21T18:50:44.000Z (about 7 years ago)
- Default Branch: main
- Last Pushed: 2024-05-01T10:38:24.000Z (6 months ago)
- Last Synced: 2024-05-01T12:30:56.061Z (6 months ago)
- Topics: airflow, argo, argo-workflows, batch-processing, cloud-native, cncf, dag, data-engineering, gitops, hacktoberfest, k8s, knative, kubernetes, machine-learning, mlops, pipelines, workflow, workflow-engine
- Language: Go
- Homepage: https://argo-workflows.readthedocs.io/
- Size: 138 MB
- Stars: 14,314
- Watchers: 201
- Forks: 3,070
- Open Issues: 1,041
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Codeowners: CODEOWNERS
- Security: SECURITY.md
- Roadmap: docs/roadmap.md
Awesome Lists containing this project
- awesome-k8s-resources - Argo Workflows - Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. (Tools and Libraries / Automation and CI/CD)
- awesome-list-docker - argo - native workflows for Kubernetes. (workflow-engine)
- awesome - argo - Argo Workflows: Get stuff done with Kubernetes. (Go)
- awesome-workflow-engines - Argo - Open source container-native workflow engine for getting work done on Kubernetes (Full fledged product)
- Awesome-AIML-Data-Ops - 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). (Data Pipeline ETL Frameworks)
- awesome-cloud-native - argo - Get stuff done with container-native workflows for Kubernetes. (Application Delivery)
README
[![Security Status](https://github.com/argoproj/argo-workflows/actions/workflows/snyk.yml/badge.svg?branch=main)](https://github.com/argoproj/argo-workflows/actions/workflows/snyk.yml?query=branch%3Amain)
[![OpenSSF Best Practices](https://bestpractices.coreinfrastructure.org/projects/3830/badge)](https://bestpractices.coreinfrastructure.org/projects/3830)
[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/argoproj/argo-workflows/badge)](https://api.securityscorecards.dev/projects/github.com/argoproj/argo-workflows)
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[![Slack](https://img.shields.io/badge/slack-argoproj-brightgreen.svg?logo=slack)](https://argoproj.github.io/community/join-slack)
[![Twitter Follow](https://img.shields.io/twitter/follow/argoproj?style=social)](https://twitter.com/argoproj)
[![LinkedIn](https://img.shields.io/badge/LinkedIn-argoproj-blue.svg?logo=linkedin)](https://www.linkedin.com/company/argoproj/)
[![Release Version](https://img.shields.io/github/v/release/argoproj/argo-workflows?label=argo-workflows)](https://github.com/argoproj/argo-workflows/releases/latest)
[![Artifact HUB](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/argo-workflows)](https://artifacthub.io/packages/helm/argo/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)](https://cncf.io/) graduated project.
## Use Cases
* [Machine Learning pipelines](https://argo-workflows.readthedocs.io/en/latest/use-cases/machine-learning/)
* [Data and batch processing](https://argo-workflows.readthedocs.io/en/latest/use-cases/data-processing/)
* [Infrastructure automation](https://argo-workflows.readthedocs.io/en/latest/use-cases/infrastructure-automation/)
* [CI/CD](https://argo-workflows.readthedocs.io/en/latest/use-cases/ci-cd/)
* [Other use cases](https://argo-workflows.readthedocs.io/en/latest/use-cases/other/)## Why Argo Workflows?
* Argo Workflows is the most popular workflow execution engine for Kubernetes.
* Light-weight, scalable, and easier to use.
* 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](https://blog.argoproj.io/argo-workflows-events-2023-user-survey-results-82c53bc30543)
## Try Argo Workflows
You can try Argo Workflows via one of the following:
1. [Interactive Training Material](https://killercoda.com/argoproj/course/argo-workflows/)
1. [Access the demo environment](https://workflows.apps.argoproj.io/workflows/argo)![Screenshot](docs/assets/screenshot.png)
## Who uses Argo Workflows?
[About 200+ organizations are officially using Argo Workflows](USERS.md)
## Ecosystem
Just some of the projects that use or rely on Argo Workflows (complete list [here](https://github.com/akuity/awesome-argo#ecosystem-projects)):
* [Argo Events](https://github.com/argoproj/argo-events)
* [Couler](https://github.com/couler-proj/couler)
* [Hera](https://github.com/argoproj-labs/hera-workflows)
* [Katib](https://github.com/kubeflow/katib)
* [Kedro](https://kedro.readthedocs.io/en/stable/)
* [Kubeflow Pipelines](https://github.com/kubeflow/pipelines)
* [Netflix Metaflow](https://metaflow.org)
* [Onepanel](https://github.com/onepanelio/onepanel)
* [Orchest](https://github.com/orchest/orchest/)
* [Piper](https://github.com/quickube/piper)
* [Ploomber](https://github.com/ploomber/ploomber)
* [Seldon](https://github.com/SeldonIO/seldon-core)
* [SQLFlow](https://github.com/sql-machine-learning/sqlflow)## Client Libraries
Check out our [Java, Golang and Python clients](docs/client-libraries.md).
## Quickstart
* [Get started here](https://argo-workflows.readthedocs.io/en/latest/quick-start/)
* [Walk-through examples](https://argo-workflows.readthedocs.io/en/latest/walk-through/)## Documentation
[View the docs](https://argo-workflows.readthedocs.io/en/latest/)
## Features
An incomplete list of features Argo Workflows provide:
* UI to visualize and manage Workflows
* Artifact support (S3, Artifactory, Alibaba Cloud OSS, Azure Blob Storage, HTTP, Git, GCS, raw)
* Workflow templating to store commonly used Workflows in the cluster
* Archiving Workflows after executing for later access
* Scheduled workflows using cron
* Server interface with REST API (HTTP and GRPC)
* DAG or Steps based declaration of workflows
* Step level input & outputs (artifacts/parameters)
* Loops
* Parameterization
* Conditionals
* Timeouts (step & workflow level)
* Retry (step & workflow level)
* Resubmit (memoized)
* Suspend & Resume
* Cancellation
* K8s resource orchestration
* Exit Hooks (notifications, cleanup)
* Garbage collection of completed workflow
* Scheduling (affinity/tolerations/node selectors)
* Volumes (ephemeral/existing)
* Parallelism limits
* Daemoned steps
* DinD (docker-in-docker)
* Script steps
* Event emission
* Prometheus metrics
* Multiple executors
* Multiple pod and workflow garbage collection strategies
* Automatically calculated resource usage per step
* Java/Golang/Python SDKs
* Pod Disruption Budget support
* Single-sign on (OAuth2/OIDC)
* Webhook triggering
* CLI
* Out-of-the box and custom Prometheus metrics
* Windows container support
* Embedded widgets
* Multiplex log viewer## Community Meetings
We host monthly community meetings where we and the community showcase demos and discuss the current and future state of the project. Feel free to join us!
For Community Meeting information, minutes and recordings, please [see here](https://bit.ly/argo-wf-cmty-mtng).Participation in Argo Workflows is governed by the [CNCF Code of Conduct](https://github.com/cncf/foundation/blob/master/code-of-conduct.md)
## Community Blogs and Presentations
* [Awesome-Argo: A Curated List of Awesome Projects and Resources Related to Argo](https://github.com/terrytangyuan/awesome-argo)
* [Automation of Everything - How To Combine Argo Events, Workflows & Pipelines, CD, and Rollouts](https://youtu.be/XNXJtxkUKeY)
* [Argo Workflows and Pipelines - CI/CD, Machine Learning, and Other Kubernetes Workflows](https://youtu.be/UMaivwrAyTA)
* [Argo Ansible role: Provisioning Argo Workflows on OpenShift](https://medium.com/@marekermk/provisioning-argo-on-openshift-with-ansible-and-kustomize-340a1fda8b50)
* [Argo Workflows vs Apache Airflow](http://bit.ly/30YNIvT)
* [CI/CD with Argo on Kubernetes](https://medium.com/@bouwe.ceunen/ci-cd-with-argo-on-kubernetes-28c1a99616a9)
* [Define Your CI/CD Pipeline with Argo Workflows](https://haque-zubair.medium.com/define-your-ci-cd-pipeline-with-argo-workflows-25aefb02fa63)
* [Distributed Machine Learning Patterns from Manning Publication](https://github.com/terrytangyuan/distributed-ml-patterns)
* [Running Argo Workflows Across Multiple Kubernetes Clusters](https://admiralty.io/blog/running-argo-workflows-across-multiple-kubernetes-clusters/)
* [Open Source Model Management Roundup: Polyaxon, Argo, and Seldon](https://www.anaconda.com/blog/developer-blog/open-source-model-management-roundup-polyaxon-argo-and-seldon/)
* [Producing 200 OpenStreetMap extracts in 35 minutes using a scalable data workflow](https://www.interline.io/blog/scaling-openstreetmap-data-workflows/)
* [Argo integration review](http://dev.matt.hillsdon.net/2018/03/24/argo-integration-review.html)
* TGI Kubernetes with Joe Beda: [Argo workflow system](https://www.youtube.com/watch?v=M_rxPPLG8pU&start=859)## Project Resources
* [Argo Project GitHub organization](https://github.com/argoproj)
* [Argo Website](https://argoproj.github.io/)
* [Argo Slack](https://argoproj.github.io/community/join-slack)## Security
See [SECURITY.md](SECURITY.md).