Argo Workflows (16,878 Stars) 2026: Kubernetes-Native Pipeline Engine with DAG and Step Execution

Argo Workflows (16,878 stars) is the Kubernetes-native workflow engine for running containerized pipelines - DAGs, steps, and cron schedules. Here is how to deploy and run your first workflow.

💡 What You Will Learn

Argo Workflows (16,878 stars) is the Kubernetes-native workflow engine for running containerized pipelines - DAGs, steps, and cron schedules. Here is how to deploy and run your first workflow.

📜 Table of Contents

• The short answer
• Key capabilities
• Deploy and run your first workflow
• Example: parallel DAG
• Practical tips
• FAQ

The short answer

argoproj/argo-workflows (16,878 stars, Go) is an open-source workflow engine for Kubernetes. Each workflow step is a container, and you define the flow as a DAG or a linear sequence. It is the de facto standard for Kubernetes-native CI/CD, ML pipelines, and batch jobs.

Key capabilities

• Container-native: every step is a Kubernetes pod
• DAG support: run steps in parallel with dependencies
• Cron workflows: schedule recurring pipelines
• Artifacts: pass data between steps via S3, GCS, or volume
• UI: web dashboard with logs, metrics and visualizations

Deploy and run your first workflow

# Install the controller
kubectl create namespace argo
kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo-workflows/master/manifests/quick-start-postgres.yaml

# Install the CLI
curl -sLO https://github.com/argoproj/argo-workflows/releases/download/v3.6.2/argo-linux-amd64.gz
gunzip argo-linux-amd64.gz && chmod +x argo-linux-amd64 && sudo mv ./argo-linux-amd64 /usr/local/bin/argo

# Submit a hello workflow
argo submit -n argo --watch https://raw.githubusercontent.com/argoproj/argo-workflows/master/examples/hello-world.yaml

Example: parallel DAG

apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: dag-
spec:
  entrypoint: main
  templates:
    - name: main
      dag:
        tasks:
          - name: build
            template: whalesay
          - name: test
            template: whalesay
            dependencies: [build]
          - name: deploy
            template: whalesay
            dependencies: [test]
    - name: whalesay
      container:
        image: docker/whalesay
        command: [cowsay, "hello"]

Practical tips

• Set resource requests/limits on every step to avoid noisy neighbors.
• Use artifact repositories (S3) for passing large files between steps.
• Monitor with argo list and the web UI; enable persistence for the controller DB.

FAQ

Do I need Kubernetes? Yes - Argo Workflows runs on Kubernetes (minikube or a real cluster).

How does it compare to Airflow? Airflow (46,389 stars) is Python-centric and VM-based; Argo is container-native and native to K8s. Pick based on your platform.

Is it free? Yes - open source (Apache-2.0).

❓ FAQ

Do I need Kubernetes?

Yes - Argo Workflows runs on Kubernetes (minikube or a real cluster).

How does it compare to Airflow?

Airflow (46,389 stars) is Python-centric and VM-based; Argo is container-native and native to K8s. Pick based on your platform.

Is it free?

Yes - open source (Apache-2.0).