Argo Workflows runs jobs made of several container-based steps. For example, a workflow might download data, process it in parallel and collect the results, starting each step only when its dependencies are ready. It gives teams a way to describe and track that whole process through Kubernetes instead of writing custom coordination scripts. This historical Argo entry refers to Workflows; Argo CD handles application deployment and is a separate tool.
Current guidance
The historical Argo entry describes Argo Workflows, the Kubernetes workflow engine. Argo CD is a separate application.
Workflows models tasks and dependencies; deployment reconciliation belongs to a different control loop. Choose the Argo Workflows chart from the Argo chart family and verify controller, executor, artifact-store and Kubernetes requirements.
Test retries, cancellation, artifact retention and permissions using a bounded workflow. A failed or retried task can repeat an external side effect, so make application tasks idempotent where required. Keep workflow ownership separate from the GitOps tool that installs it.
Historical upstream link check · 2026-10-09
The recorded upstream address responded successfully (HTTP 200) on 2026-10-09. Link availability does not certify the historical installation instructions or current security support.
Website availability is separate from project, chart and image support. Use the current guidance and primary sources on this page to assess the distribution.
Historical Kubedex content
Original publication: 2018-09-28T05:04:40+00:00. Preserved for context. Commands, versions, prices and results below reflect the original research.
Argo is an open source container-native workflow engine for getting work done on Kubernetes. Argo 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?
- Argo is designed from the ground up for containers without the overhead and limitations of legacy VM and server-based environments.
- Argo is cloud agnostic and can run on any kubernetes cluster.
- Argo with Kubernetes puts a cloud-scale supercomputer at your fingertips.
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
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Sources & further reading
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