Argo Workflows is a Kubernetes-native workflow engine that defines workflows as Directed Acyclic Graphs (DAGs) or sequential steps using Custom Resource Definitions (CRDs). Each workflow step runs in its own container, making it ideal for CI/CD pipelines, ML training, data processing, and any containerized batch workload. This cheat sheet covers the full workflow specification, template types, artifact management, concurrency, observability, and the broader Argo ecosystem.
What This Cheat Sheet Covers
This topic spans 17 focused tables and 149 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Core Concepts and Architecture
Argo Workflows runs inside Kubernetes and manages workflows as CRDs. Understanding the key components — controller, server, executor, and CRD kinds — is the foundation for all subsequent concepts.
| Concept | Example / Value | Description |
|---|---|---|
kind: Workflow | The core Kubernetes custom resource representing a single workflow execution instance with a unique name. | |
kind: WorkflowTemplate | A reusable, namespace-scoped template library that other workflows can reference via templateRef. | |
kind: ClusterWorkflowTemplate | Like WorkflowTemplate but cluster-scoped, accessible from any namespace. | |
kind: CronWorkflow | • Triggers a Workflow on a cron schedule • supports multiple schedules, timezone, and concurrencyPolicy | |
workflow-controller Deployment | • Reconciliation loop watching Workflow CRDs • schedules pods and reconciles one workflow at a time per controller |