Argo Workflows on Kubernetes – Core Concepts

Argo Workflows on Kubernetes - Core Concepts

Argo Workflows on Kubernetes – Core Concepts

Learn how to orchestrate Kubernetes-native workflows with Argo Workflows.

Language: english

Note: 4.6/5 (119 notes) 3,907 students

Instructor(s): Jan Schwarzlose

Last update: 2021-05-01

What you’ll learn

  • You will learn how to install a minikube cluster with Argo Workflows on your local machine.
  • You will get to know the core concepts of Argo Workflows and how to use them creating workflows.
  • You will be able to communicate with the Argo server using the kubectl CLI and how to use the Argo Server UI.

 

Requirements

  • Basic knowledge of Kubernetes is desirable, but not essential.

 

Argo Workflows on Kubernetes - Core ConceptsArgo Workflows on Kubernetes - Core Concepts

 

Description

This is an introductory course to the full course Hands-On Guide to Argo Workflows on Kubernetes.

Argo Workflows is a container native workflow engine for orchestrating jobs in Kubernetes. This means that complex workflows can be created and executed completely in a Kubernetes cluster.

It provides a mature user interface, which makes operation and monitoring very easy and clear. There is native artifact support, whereby it is possible to use completely different artifact repositories (Minio, AWS S3, Artifactory, HDFS, OSS, HTTP, Git, Google Cloud Service, raw).

Templates and cron workflows can be created, with which individual components can be created and combined into complex workflows. This means that composability is given. Furthermore, workflows can be archived and Argo provides a REST API and an Argo CLI tool, which makes communication with the Argo server easy.

It is also worth mentioning that Argo Workflows can be used to manage thousands of parallel pods and workflows within a Kubernetes cluster. And robust repetition mechanisms ensure a high level of reliability.

There is already a large, global community that is growing steadily. Just to name IBM, SAP and NVIDIA. It is mainly used for machine learning, ETL, Batch – and data processing and for CI / CD. And what is also very important – it is open source and a project of the Cloud Native Computing Foundation.


Upon successful completion of the course, you will be able to create workflows using the core concepts of Argo Workflows. You will be confident to use the kubectl CLI and the Argo Server UI in order to communicate with the Argo Server and manage your workflows.

 

Argo Workflows on Kubernetes - Core Concepts

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Who this course is for

  • Anyone who wants to use a Kubernetes native orchestration tool to create simple and complex workflows.
  • Everyone who wants to get to know most of the features of Argo Workflows for the creation of large workflows with a practical approach.

 

Course content

  • Introduction
    • Introduction
  • Create a Minikube Cluster
    • Create a Minikube Cluster – Introduction
    • Installation kubectl – Windows 10
    • Installation minikube – Windows 10
    • Select a hypervisor – Windows 10
    • Enable Hyper-V – Windows 10
    • Start minikube with Hyper-V – Windows 10
  • First Steps and Core Concepts
    • Changes
    • Installation Argo Workflows
    • Argo Server User Interface
    • Hello World Workflow
    • Core Concept
    • Template Definitions
    • Container Template
    • Script Template
    • Rating
    • Resource Template
    • Template Invocators
    • Steps Template serial
    • Steps Template parallel
    • Suspend Template
    • DAG Template
  • Summary
    • Summary

 


 

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