Template for basic Argo Workflow

Backstage Template for Basic Argo Workflow with Spark Job

This Backstage template YAML automates the creation of an Argo Workflow for Kubernetes that includes a basic Spark job, providing a convenient way to configure and deploy workflows involving data processing or machine learning jobs. Users can define key parameters, such as the application name and the path to the main Spark application file. The template creates necessary Kubernetes resources, publishes the application code to a Gitea Git repository, registers the application in the Backstage catalog, and deploys it via ArgoCD for easy CI/CD management.

Use Case

This template is designed for teams that need a streamlined approach to deploy and manage data processing or machine learning jobs using Spark within an Argo Workflow environment. It simplifies the deployment process and integrates the application with a CI/CD pipeline. The template performs the following:

• Workflow and Spark Job Setup: Defines a basic Argo Workflow and configures a Spark job using the provided application file path, ideal for data processing tasks.
• Repository Setup: Publishes the workflow configuration to a Gitea repository, enabling version control and easy updates to the job configuration.
• ArgoCD Integration: Creates an ArgoCD application to manage the Spark job deployment, ensuring continuous delivery and synchronization with Kubernetes.
• Backstage Registration: Registers the application in Backstage, making it easily discoverable and manageable through the Backstage catalog.

This template boosts productivity by automating steps required for setting up Argo Workflows and Spark jobs, integrating version control, and enabling centralized management and visibility, making it ideal for projects requiring efficient deployment and scalable data processing solutions.