Argo Workflows is a container-native workflow engine for Kubernetes that allows you to orchestrate parallel jobs and manage complex computational workflows. It solves several key problems:

• Pipeline orchestration: Manages complex multi-step workflows with dependencies
• Resource management: Efficiently utilizes Kubernetes resources for batch processing
• Scalability: Handles thousands of concurrent workflow executions
• Reliability: Provides built-in retry mechanisms and error handling
• Artifact management: Handles input/output artifacts between workflow steps

Each workflow is defined as a Kubernetes Custom Resource Definition (CRD), making it cloud-native and leveraging Kubernetes' scheduling and resource management capabilities.

The main components include:

• Workflow Controller: The core component that manages workflow execution, watches for new workflows, and orchestrates their execution
• Argo Server: Provides a REST API and web UI for managing workflows
• Executor: Runs inside each workflow pod to manage the container lifecycle and artifact collection
• CLI (argo): Command-line interface for submitting and managing workflows
• Workflow CRD: Kubernetes Custom Resource Definition that defines the workflow specification

• Workflow: A specific instance of a workflow execution with concrete parameters and runtime information. It's like running a specific job.

• WorkflowTemplate: A reusable workflow definition that can be instantiated multiple times with different parameters. It's like a blueprint or template.

# WorkflowTemplate - reusable template
apiVersion: argoproj.io/v1alpha1
kind: WorkflowTemplate
metadata:
  name: hello-world-template
spec:
  entrypoint: whalesay
  templates:
  - name: whalesay
    container:
      image: docker/whalesay
      command: [cowsay]
      args: ["{{workflow.parameters.message}}"]

# Workflow - specific instance
apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: hello-world-
spec:
  workflowTemplateRef:
    name: hello-world-template
  arguments:
    parameters:
    - name: message
      value: "Hello DevOps Team!"