Learn ARGO-WORKFLOWS with Real Code Examples

Argo Workflows allows users to define multi-step workflows declaratively using YAML manifests.

Each step runs as a Kubernetes pod, allowing containerized tasks with resource isolation.

Supports DAG (Directed Acyclic Graph) and step-based workflows for complex dependencies.

Integrates natively with Kubernetes for scheduling, scaling, and resource management.

Can be used for CI/CD pipelines, data processing, machine learning workflows, and batch jobs.

Workflow as Kubernetes custom resources

Containerized execution for each step

Support for parallel and sequential tasks

Input/output artifact management

Integration with Kubernetes RBAC, secrets, and config maps

Workflow - top-level definition of a set of steps

Template - reusable step or DAG component

Step - single container task in a workflow

DAG - Directed Acyclic Graph defining dependencies between steps

Artifact - data passed between workflow steps

workflows/ - YAML manifests defining workflows

templates/ - reusable workflow components

scripts/ - scripts executed inside workflow steps

artifacts/ - data files used or produced by workflows

README.md - workflow documentation and usage instructions

Write YAML workflow manifest

Define steps or DAG with dependencies

Specify container images, commands, and resources

Submit workflow via Argo CLI or Kubernetes API

Monitor workflow execution via UI or CLI

Beginner: single-step workflow

Intermediate: multi-step sequential workflow

Advanced: DAG workflow with parallel tasks

Expert: loops, conditional execution, and artifact passing

Enterprise: large-scale ML/ETL pipelines with cron triggers

Argo Workflows vs Jenkins: container-native vs general-purpose CI

Argo Workflows vs Tekton: Kubernetes-native DAG orchestration

Argo Workflows vs GitHub Actions: full Kubernetes control vs SaaS CI

Argo Workflows vs Airflow: DAG scheduling on Kubernetes vs traditional workflow engine

Argo Workflows vs Nomad: container workflows vs general workload orchestration

2017 - Initial release by Intuit

2018 - Open-sourced and accepted into CNCF sandbox

2019 - Support for DAG workflows and artifact passing

2020 - Cron workflows and events integration

2025 - Continued development and enterprise adoption

Workflow - top-level Kubernetes resource for tasks

Template - reusable task definition

Step - single container task

DAG - Directed Acyclic Graph of steps

Artifact - data passed between steps