Use Argo CLI to create a workflow in an ACK cluster - Container Service for Kubernetes

Argo Workflows is a Kubernetes-native workflow engine that orchestrates parallel tasks using YAML files or Python SDK, thus simplifying the automation and management of containerized applications. Argo Workflows is suitable for scenarios requiring multi-step processes, parallel tasks, and dependencies, such as data processing, machine learning pipelines, simulation computing, and Continuous Integration and Continuous Delivery (CICD) pipelines. This topic uses a sample application to demonstrate how to create a workflow using Argo CLI.

Prerequisites

The Argo Workflow component and Alibaba Cloud Argo CLI are installed. For more information, see Enable batch task orchestration.

Procedure

Use the following YAML template to create a file named helloworld-workflow.yaml. This file is used to submit a sample workflow task.

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" ]

Run the following command to submit the workflow:
```
argo submit helloworld-workflow.yaml -n argo
```

Check the status of the workflow.

Run the following command to get the list of workflows:

argo list -n argo

Expected output:

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

This output indicates that the workflow is complete.

Run the following command to check the status of the workflow:

argo get hello-world-XXXXX -n argo

Expected output:

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

This output also confirms that the workflow is complete.

Reference

Resources related to workflows are periodically deleted. To make them persistent in a database, see Workflow persistence.