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Argo Getting Started

To see how Argo works, you can run examples of simple workflows and workflows that use artifacts. For the latter, you'll set up an artifact repository for storing the artifacts that are passed in the workflows. Here are the requirements and steps to run the workflows.

Requirements

  • Installed Kubernetes 1.9 or later
  • Installed kubectl
  • Have a kubeconfig file (default location is ~/.kube/config).

1. Download Argo

Download the latest Argo binary version from https://github.com/argoproj/argo/releases/latest.

Also available in Mac Homebrew:

brew install argoproj/tap/argo

Also you can use this command to install for Linux

curl -sSL -o /usr/local/bin/argo https://github.com/argoproj/argo/releases/download/v2.3.0/argo-linux-amd64
chmod +x /usr/local/bin/argo

2. Install the Controller and UI

kubectl create namespace argo
kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo/stable/manifests/install.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

3. Configure the service account to run workflows

To run all of the examples in this guide, the 'default' service account is too limited to support features such as artifacts, outputs, access to secrets, etc... For demo purposes, run the following command to grant admin privileges to the 'default' service account in the namespace 'default':

kubectl create rolebinding default-admin --clusterrole=admin --serviceaccount=argo:default

For the bare minimum set of privileges which a workflow needs to function, see Workflow RBAC. You can also submit workflows which run with a different service account using:

argo submit --serviceaccount <name>

4. Run Simple Example Workflows

argo submit --watch https://raw.githubusercontent.com/argoproj/argo/master/examples/hello-world.yaml
argo submit --watch https://raw.githubusercontent.com/argoproj/argo/master/examples/coinflip.yaml
argo submit --watch https://raw.githubusercontent.com/argoproj/argo/master/examples/loops-maps.yaml
argo list
argo get xxx-workflow-name-xxx
argo logs xxx-pod-name-xxx #from get command above

You can also create workflows directly with kubectl. However, the Argo CLI offers extra features that kubectl does not, such as YAML validation, workflow visualization, parameter passing, retries and resubmits, suspend and resume, and more.

kubectl create -f https://raw.githubusercontent.com/argoproj/argo/master/examples/hello-world.yaml
kubectl get wf
kubectl get wf hello-world-xxx
kubectl get po --selector=workflows.argoproj.io/workflow=hello-world-xxx --show-all
kubectl logs hello-world-yyy -c main

Additional examples are available here.

5. Install an Artifact Repository

Argo supports S3 (AWS, GCS, Minio) as well as Artifactory as artifact repositories. This tutorial uses Minio for the sake of portability. Instructions on how to configure other artifact repositories are here.

helm install stable/minio \
  --name argo-artifacts \
  --set service.type=LoadBalancer \
  --set defaultBucket.enabled=true \
  --set defaultBucket.name=my-bucket \
  --set persistence.enabled=false \
  --set fullnameOverride=argo-artifacts

Login to the Minio UI using a web browser (port 9000) after exposing obtaining the external IP using kubectl.

kubectl get service argo-artifacts -o wide

On Minikube:

minikube -n argo service --url argo-artifacts

NOTE: When minio is installed via Helm, it uses the following hard-wired default credentials, which you will use to login to the UI:

  • AccessKey: AKIAIOSFODNN7EXAMPLE
  • SecretKey: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

Create a bucket named my-bucket from the Minio UI.

6. Reconfigure the workflow controller to use the Minio artifact repository

Edit the workflow-controller config map to reference the service name (argo-artifacts) and secret (argo-artifacts) created by the helm install:

kubectl edit cm -n argo workflow-controller-configmap
...
data:
  config: |
    artifactRepository:
      s3:
        bucket: my-bucket
        endpoint: argo-artifacts:9000
        insecure: true
        # accessKeySecret and secretKeySecret are secret selectors.
        # It references the k8s secret named 'argo-artifacts'
        # which was created during the minio helm install. The keys,
        # 'accesskey' and 'secretkey', inside that secret are where the
        # actual minio credentials are stored.
        accessKeySecret:
          name: argo-artifacts
          key: accesskey
        secretKeySecret:
          name: argo-artifacts
          key: secretkey

NOTE: the Minio secret is retrieved from the namespace you use to run workflows. If Minio is installed in a different namespace then you will need to create a copy of its secret in the namespace you use for workflows.

7. Run a workflow which uses artifacts

argo submit https://raw.githubusercontent.com/argoproj/argo/master/examples/artifact-passing.yaml

8. Access the Argo UI

By default, the Argo UI service is not exposed with an external IP. To access the UI, use one of the following methods:

Method 1: kubectl port-forward

kubectl -n argo port-forward deployment/argo-ui 8001:8001

Then visit: http://127.0.0.1:8001

Method 2: kubectl proxy

kubectl proxy

Then visit: http://127.0.0.1:8001/api/v1/namespaces/argo/services/argo-ui/proxy/

NOTE: artifact download and webconsole is not supported using this method

Method 3: Expose a LoadBalancer

Update the argo-ui service to be of type LoadBalancer.

kubectl patch svc argo-ui -n argo -p '{"spec": {"type": "LoadBalancer"}}'

Then wait for the external IP to be made available:

kubectl get svc argo-ui -n argo
NAME      TYPE           CLUSTER-IP      EXTERNAL-IP     PORT(S)        AGE
argo-ui   LoadBalancer   10.19.255.205   35.197.49.167   80:30999/TCP   1m

NOTE: On Minikube, you won't get an external IP after updating the service -- it will always show pending. Run the following command to determine the Argo UI URL:

minikube service -n argo --url argo-ui