Use the Argo CLI to create workflows in an ACS cluster - Container Compute Service

Argo Workflows is a Kubernetes-native workflow engine. It allows you to use YAML or Python to orchestrate concurrent jobs in order to simplify the automation and management of containerized applications. Argo Workflows is suitable for handling multiple steps, concurrent jobs, and dependencies, such as data processing, machine learning pipelines, simulation computing, and CI/CD pipelines. This topic describes how to use the Argo CLI to create a workflow.

Prerequisites

Refer to Enable batch job orchestration to install the component and Alibaba Cloud Argo CLI.

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.

References

Resources used by workflows are periodically deleted. To persist workflows to databases, see Persist workflows.