To see how Argo Workflows work, you can install it and run examples of simple workflows.
Before you start you need a Kubernetes cluster and kubectl
set up to be able to access that cluster. For the purposes of getting up and running, a local cluster is fine. You could consider the following local Kubernetes cluster options:
Alternatively, if you want to try out Argo Workflows and don't want to set up a Kubernetes cluster, try the Killercoda course.
To install Argo Workflows, navigate to the releases page and find the release you wish to use (the latest full release is preferred).
Scroll down to the Controller and Server
section and execute the kubectl
commands.
Below is an example of the install commands, ensure that you update the command to install the correct version number:
kubectl create namespace argo
kubectl apply -n argo -f https://github.com/argoproj/argo-workflows/releases/download/v<<ARGO_WORKFLOWS_VERSION>>/install.yaml
The argo-server (and thus the UI) defaults to client authentication, which requires clients to provide their Kubernetes bearer token in order to authenticate. For more information, refer to the Argo Server Auth Mode documentation. We will switch the authentication mode to server
so that we can bypass the UI login for now:
kubectl patch deployment \
argo-server \
--namespace argo \
--type='json' \
-p='[{"op": "replace", "path": "/spec/template/spec/containers/0/args", "value": [
"server",
"--auth-mode=server"
]}]'
Open a port-forward so you can access the UI:
kubectl -n argo port-forward deployment/argo-server 2746:2746
This will serve the UI on https://localhost:2746. Due to the self-signed certificate, you will receive a TLS error which you will need to manually approve.
Next, Download the latest Argo CLI from the same releases page.
argo submit -n argo --watch https://raw.githubusercontent.com/argoproj/argo-workflows/master/examples/hello-world.yaml
The --watch
flag used above will allow you to observe the workflow as it runs and the status of whether it succeeds.
When the workflow completes, the watch on the workflow will stop.
You can list all the Workflows you have submitted by running the command below:
argo list -n argo
You will notice the Workflow name has a hello-world-
prefix followed by random characters. These characters are used
to give Workflows unique names to help identify specific runs of a Workflow. If you submitted this Workflow again,
the next Workflow run would have a different name.
Using the argo get
command, you can always review details of a Workflow run. The output for the command below will
be the same as the information shown as when you submitted the Workflow:
argo get -n argo @latest
The @latest
argument to the CLI is a short cut to view the latest Workflow run that was executed.
You can also observe the logs of the Workflow run by running the following:
argo logs -n argo @latest
- Open a port-forward so you can access the UI:
kubectl -n argo port-forward deployment/argo-server 2746:2746
-
Navigate your browser to https://localhost:2746.
-
Click
+ Submit New Workflow
and thenEdit using full workflow options
-
You can find an example workflow already in the text field. Press
+ Create
to start the workflow.