To see how Argo works, you can install it and run examples of simple workflows and workflows that use artifacts.
Firstly, you'll need a Kubernetes cluster and kubectl set-up
To get started quickly, you can use the quick start manifest which will install Argo Workflow as well as some commonly used components:
!!! note These manifests are intended to help you get started quickly. They are not suitable in production, on test environments, or any environment containing any real data. They contain hard-coded passwords that are publicly available.
kubectl create ns argo
kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo-workflows/master/manifests/quick-start-postgres.yaml!!! note
On GKE, you may need to grant your account the ability to create new clusterroles
kubectl create clusterrolebinding YOURNAME-cluster-admin-binding --clusterrole=cluster-admin --user=YOUREMAIL@gmail.com!!! note
To run Argo on GKE Autopilot, you must use the emissary executor or the k8sapi executor. Find more information on our executors doc.
If you are running Argo Workflows locally (e.g. using Minikube or Docker for Desktop), open a port-forward so you can access the namespace:
kubectl -n argo port-forward deployment/argo-server 2746:2746This will serve the user interface on https://localhost:2746
If you're using running Argo Workflows on a remote cluster (e.g. on EKS or GKE) then follow these instructions.
Next, Download the latest Argo CLI from our releases page.
Finally, submit an example workflow:
argo submit -n argo --watch https://raw.githubusercontent.com/argoproj/argo-workflows/master/examples/hello-world.yaml
argo list -n argo
argo get -n argo @latest
argo logs -n argo @latest