OpenShift is a rock solid platform engineered for the enterprise. It's built on top of Kubernetes and provides many value add features, tools, and services which help to streamline the complete end-to-end container development and deployment lifecycle.
This introductory level training course is designed to bring you quickly up to speed with the key features that OpenShift provides. You'll then get to observe first hand how to launch a new OpenShift Container Platform 4.2 cluster on AWS and then deploy a real world cloud native application into it.
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Learning Objectives
By completing this course, you will:
- Learn and understand what OpenShift is and what it brings to the table
- Learn and understand how to provision a brand new OpenShift 4.2 cluster on AWS
- Learn and understand the basic principles of deploying a cloud native application into OpenShift
- Understand how to work with and configure many of the key OpenShift value add cluster resources
- Learn how to work with the OpenShift web administration console to manage and administer OpenShift deployments
- Learn how to work with the oc command line tool to manage and administer OpenShift deployments
- And finally, you’ll learn how to manage deployments and OpenShift resources through their full lifecycle
Intended Audience
This course is intended for:
- Anyone interested in learning OpenShift
- Software Developers interested in OpenShift containerisation, orchestration, and scheduling
- DevOps practitioners looking to learn how to provision and manage and maintain applications on OpenShift
Prerequisites
To get the most from this course, you should have at least:
- A basic understanding of containers and containerisation
- A basic understanding of Kubernetes - and container orchestration and scheduling
- A basic understanding of software development and the software development life cycle
- A basic understanding of networks and networking
Source Code
This course references the following CloudAcademy GitHub hosted repos:
- https://github.com/cloudacademy/openshift-voteapp-demo (OpenShift VoteApp Runbook)
- https://github.com/cloudacademy/openshift-s2i-frontendbuilder (OpenShift S2I Frontend Builder)
- https://github.com/cloudacademy/openshift-voteapp-frontend-react (VoteApp Frontend UI)
- [Jeremy] Okay, welcome back. Before getting into the specifics of deploying the frontend resources, I want to take the opportunity to use the frontend to demonstrate the excellent S2I or Source to Image technology, for building and compiling custom container images. In our case, I will use S2I to create a custom frontend container image. Now, the frontend web interface has been engineered using the React framework, which helps with building component-based UIs. I'll therefore use S2I to perform the transpilation process required to convert the JSX source into pure HTML, JavaScript and CSS servable assets. This overall process will become clearer as we progress through the next set of steps.
But, for starters, I'll need to set up and install the OpenShift S2I command line utility. Let's do this now. Let's jump back into the runsheet, and copy the installation commands from step 17. And then run them within the terminal, like so. This completes the installation, and we can now test the S2I utility. This simply prints out the usage information. For example we can print out the version information by running the command "s2i version." Here we can see that we are using version 1.2.0. If you are interested in reviewing more information about the S2I utility, then consider reading the following documentation found here.
Okay, that completes step 17. This has downloaded, extracted, and moved the S2I utility onto the local systems path so that it can be called up from anywhere within the terminal.
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).