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) graduated project.
Use Cases
- Machine Learning pipelines
- Data and batch processing
- Infrastructure automation
- CI/CD
- Other use cases
Why Argo Workflows?
- Argo Workflows is the most popular workflow execution engine for Kubernetes.
- Light-weight, scalable, and easier to use.
- Including for Python users through the Hera Python SDK for 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.
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Try Argo Workflows
You can try Argo Workflows via one of the following:
- Interactive Training Material
- Access the demo environment
Who uses Argo Workflows?
About 200+ organizations are officially using Argo Workflows
Ecosystem
Just some of the projects that use or rely on Argo Workflows (complete list here):
- Argo Events
- Hera
- Katib
- Kedro
- Kubeflow Pipelines
- Netflix Metaflow
- Piper
- Seldon
- SQLFlow