Workflows & Pipelines

Container native workflow engine for Kubernetes supporting both DAG and step based workflows.

Docs

slack

Argoproj - Get stuff done with Kubernetes

Argo Image

News

KubeCon 2018 in Seattle was the biggest KubeCon yet with 8000 developers attending. We connected with many existing and new Argoproj users and contributions, and gave away a lot of Argo T-shirts at our booth sponsored by Intuit!

We were also super excited to see KubeCon presentations about Argo by Argo developers, users and partners.

If you actively use Argo in your organization and your organization would be interested in participating in the Argo Community, please ask a representative to contact saradhi_sreegiriraju@intuit.com for additional information.

What is Argoproj?

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

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!

Documentation

Features

  • 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

Who uses Argo?

As the Argo Community grows, we'd like to keep track of our users. Please send a PR with your organization name.

Currently officially using Argo:

  1. Admiralty
  2. Adobe
  3. Alibaba Cloud
  4. BlackRock
  5. Canva
  6. CoreFiling
  7. Cratejoy
  8. Cyrus Biotechnology
  9. Datadog
  10. Equinor
  11. Gardener
  12. Gladly
  13. GitHub
  14. Google
  15. Interline Technologies
  16. Intuit
  17. Karius
  18. KintoHub
  19. Localytics
  20. NVIDIA
  21. Preferred Networks
  22. Quantibio
  23. SAP Hybris
  24. Styra

Community Blogs and Presentations

Project Resources