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    Container Service for Kubernetes:Create a workflow using the Argo CLI

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    Container Service for Kubernetes:Create a workflow using the Argo CLI

    Last Updated:Mar 26, 2026

    This topic walks you through creating and running a hello-world workflow on your ACK cluster using Argo CLI.

    Prerequisites

    Before you begin, ensure that you have:

    How it works

    If you have ever run a container with Docker, an Argo workflow does the same thing—but on a Kubernetes cluster:

    docker run mirrors-ssl.aliyuncs.com/busybox:latest echo "hello world"

    An Argo workflow wraps that container run in a Kubernetes resource. Instead of a CLI command, you define the container, its command, and its arguments in a YAML file, then submit it to the cluster.

    Create and run a workflow

    Step 1: Define the workflow

    Create a file named helloworld-workflow.yaml with the following content:

    apiVersion: argoproj.io/v1alpha1
kind: Workflow                # Defines a new Kubernetes resource type for Argo Workflows.
metadata:
  generateName: hello-world-  # The prefix for the workflow name. Kubernetes will append a unique suffix.
spec:
  entrypoint: main            # Specifies the template to execute first.
  templates:
    - name: main              # The name of the template.
      container:
        image: mirrors-ssl.aliyuncs.com/busybox:latest
        command: [ echo ]
        args: [ "hello world" ]

    Key fields:

    Field Description
    kind: Workflow Declares this as an Argo workflow resource in Kubernetes.
    generateName Sets the name prefix. Kubernetes appends a random suffix, producing a unique name like hello-world-k8pz2 for each submission.
    entrypoint Specifies which template runs first. In a multi-step workflow, this is where execution begins.
    templates Defines the units of work. Each template can be a container, a script, or a sequence of steps.

    Step 2: Submit the workflow

    Run the following command to submit the workflow to the argo namespace:

    argo submit helloworld-workflow.yaml -n argo

    Step 3: Check the workflow status

    1. List all workflows in the namespace:

      argo list -n argo

      The output is similar to:

      NAME                STATUS      AGE   DURATION   PRIORITY
hello-world-XXXXX   Succeeded   2m    37s        0

      A Succeeded status confirms the workflow completed.

    2. Get the full details of the workflow:

      argo get hello-world-XXXXX -n argo

      The output is similar to:

      Name:                hello-world-XXXXX
Namespace:           argo
ServiceAccount:      unset (will run with the default ServiceAccount)
Status:              Succeeded
Conditions:
 PodRunning          False
 Completed           True
....
Duration:            37 seconds
Progress:            1/1
ResourcesDuration:   17s*(1 cpu),17s*(100Mi memory)

STEP                  TEMPLATE  PODNAME            DURATION  MESSAGE
 ✔ hello-world-XXXXX  whalesay  hello-world-XXXXX  27s

      Status: Succeeded and Completed: True confirm the workflow ran to completion.

    Argo CLI quick reference

    Operation Command
    Submit a workflow argo submit <file>.yaml -n argo
    List all workflows argo list -n argo
    Get details of a specific workflow argo get <workflow-name> -n argo

    What's next

    Workflow resources are periodically deleted from the cluster. To persist workflow records in a database, see Workflow persistence.

    References