December 10, 2019

475 words 3 mins read



Argo Workflows: Get stuff done with Kubernetes.

repo name argoproj/argo
repo link
language Go
size (curr.) 24022 kB
stars (curr.) 4772
created 2017-08-21
license Apache License 2.0


Argoproj - Get stuff done with Kubernetes

Argo Image


kubectl create namespace argo
kubectl apply -n argo -f

What is Argoproj?

Argoproj is a collection of tools for getting work done with Kubernetes.

  • Argo Workflows - Container-native Workflow Engine
  • Argo CD - Declarative GitOps Continuous Delivery
  • Argo Events - Event-based Dependency Manager
  • Argo Rollouts - Progressive Delivery with support for Canary and Blue Green deployment strategies

Also argoproj-labs is a separate GitHub org that we setup for community contributions related to the Argoproj ecosystem. Repos in argoproj-labs are administered by the owners of each project. Please reach out to us on the Argo slack channel if you have a project that you would like to add to the org to make it easier to others in the Argo community to find, use, and contribute back.

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 in the workflow is a container.
  • Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a graph (DAG).
  • Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes.
  • Run CI/CD pipelines natively on Kubernetes without configuring complex software development products.

Why 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.
  • Easily orchestrate highly parallel jobs on Kubernetes.
  • Argo Workflows puts a cloud-scale supercomputer at your fingertips!

Who uses Argo Workflows?

Official Argo Workflows user list



  • DAG or Steps based declaration of workflows
  • Artifact support (S3, Artifactory, HTTP, Git, raw)
  • 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

Community Blogs and Presentations

Project Resources

comments powered by Disqus