ipelines ](https://github.com/kubeflow/pipelines)
  * [ Netflix Metaflow ](https://metaflow.org)
  * [ Onepanel ](https://www.onepanel.ai/)
  * [ Orchest ](https://github.com/orchest/orchest/)
  * [ Piper ](https://github.com/rookout/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 ](client-libraries/) .

##  Quickstart  ¶

  * [ Get started here ](quick-start/)
  * [ Walk-through examples ](walk-through/)

##  Documentation  ¶

You're here!

##  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 ext