Training > Cloud & Containers > DevOps and Workflow Management with Argo (LFS256)
Training Course

DevOps and Workflow Management with Argo (LFS256)

Learn to streamline Kubernetes workflows with Argo tools.

Who Is It For

Tailored for DevOps engineers, software developers, SysAdmins, and IT managers, this course teaches skills in Kubernetes workflow management, streamlined deployments, and GitOps practices.
read less read more
What You’ll Learn

Learn Argo for seamless Kubernetes workflows: deploy apps, manage rollouts, implement RBAC, troubleshoot, leverage event-driven architecture, and optimize with the Argo CLI.
read less read more
What It Prepares You For

By the end of this course, you’ll be well-equipped to implement Argo to manage complex deployments and workflows. It will also help you prepare for the Certified Argo Project Associate (CAPA) exam, along with real-life experience and additional study.
read less read more
Course Outline
Chapter 1. Course Introduction
Chapter 2. Introduction to Argo
Chapter 3. Argo CD
Chapter 4. Argo Workflows
Chapter 5. Argo Rollouts
Chapter 6. Argo Events

Prerequisites
To make the most out of this course, you should have the following knowledge and skills:

  • Kubernetes basics: Familiarity with Kubernetes concepts such as Pods, Services, Deployments, and Namespaces is crucial. Understanding how to create and manage these resources will be beneficial. We recommend Introduction to Kubernetes (LFS158x), free to audit on edX
  • YAML manifests: Since Argo uses YAML for configuration and defining workflows, a good understanding of YAML syntax and how to write Kubernetes manifests in YAML is required.
  • Imperative vs Declarative configuration: Knowledge of these two approaches to configuration management in Kubernetes is important. Argo uses a declarative approach, so understanding the difference between the two will be helpful.
  • GitOps practices: As Argo is a tool that enables GitOps practices in Kubernetes, having an understanding of GitOps principles and practices would be beneficial.
  • Command Line Interface (CLI) usage: Basic skills in using the command line interface are necessary as the course includes hands-on labs that require interaction with Argo’s CLI.
  • Basic programming skills: While not strictly necessary, having basic programming skills can help in understanding some of the more advanced concepts in the course, such as parameterization and conditionals in Argo Workflows.
Lab Info
You will need to meet the following system requirements:

  • Operating System: A modern operating system capable of running Docker and Kubernetes. This could be Linux (Ubuntu, CentOS), macOS, or Windows 10 Pro/Enterprise/Education with Hyper-V enabled.
  • Hardware: At least 8GB of RAM (16GB recommended) and a minimum of 20GB of free disk space. These specifications are necessary to run a local Kubernetes cluster using a lightweight distribution like K3s. If your system does not meet these requirements, we recommend using the free tier of a public cloud provider like AWS, GCP, or Azure.
  • Software:
    • Docker: Docker is used to run containers. Install the latest stable version.
    • Kubernetes: You can install a local Kubernetes cluster using a lightweight distribution like K3s. The course will cover the setup of a local Kubernetes cluster.
    • kubectl: The Kubernetes command-line tool, kubectl, allows you to run commands against Kubernetes clusters.
    • Argo CLI: The Argo command-line tool will be used to interact with Argo components.
    • Code editor: A text editor or IDE that supports YAML for editing configuration files and manifests, such as Visual Studio Code.

Please note that while you can choose to use another distribution like managed Kubernetes by public cloud services like AWS, GCP or Azure, this course does not cover the setup of them. Specific labs might have additional requirements which will be specified in the lab instructions.