Argo Workflows on Ubuntu 24.04

Argo Workflows is a fully Kubernetes-native workflow orchestration engine designed to run and manage complex workflows as custom resources within a Kubernetes cluster. It enables users to define, execute, and monitor multi-step workflows using declarative YAML, making it ideal for CI/CD pipelines, data processing, machine learning workflows, and batch jobs.

Argo Workflows leverages Kubernetes primitives to provide scalable, reliable, and cloud-native workflow execution. Each workflow step runs as a container, allowing seamless integration with existing containerized applications and Kubernetes infrastructure.

Common use cases include:

• CI/CD pipelines and build automation
• Batch processing and scheduled jobs
• Data engineering and ETL workflows
• Machine learning training and inference pipelines
• Microservices orchestration and automation

Features of Argo Workflows:

• Kubernetes-native workflow engine using Custom Resource Definitions (CRDs)
• Declarative workflow definitions using YAML
• Step-based, DAG-based, and event-driven workflows
• Scalable execution with Kubernetes scheduling
• Built-in retry logic, conditional execution, and artifacts support
• CLI and web-based UI for workflow submission and monitoring

To verify Argo Workflows installation and usage, use the following steps:

Check Kubernetes cluster:
$ kubectl cluster-info

List Argo workflows:
$ kubectl get workflows -n argo

Create a workflow:
$ kubectl create -n argo -f workflow.yaml

View workflow logs:
$ kubectl logs -n argo -l workflows.argoproj.io/workflow

Check version and Run Argo Workflows :
$ sudo su
$ argo version 
$ kubectl rollout restart deployment argo-server -n argo
$ kubectl -n argo create token argo-server
$ kubectl port-forward --address 0.0.0.0 svc/argo-server -n argo 2746:2746

To Access Argo Workfows Web UI :

 Hit on Browser:https://your_ip:2746

Disclaimer: Argo Workflows is an open-source Kubernetes-native workflow engine. This product requires an existing Kubernetes cluster and does not operate as a standalone service. Users are responsible for cluster configuration, RBAC permissions, workflow definitions, monitoring, and cost management of the underlying Kubernetes infrastructure.