Course Syllabus

Get the most from GitHub, the industry-standard tool for collaborating on and sharing code. Learn how to use features that support and enhance the modern software pipeline. This course shows developers how to extend their use of GitHub and how to leverage the GitHub ecosystem to customize and enhance existing workflows. Instructor Aaron Stewart, training content specialist at GitHub, explains important concepts such as managing organizations and teams, enabling continuous integration and delivery, conducting code reviews, and using branch protections. Plus, discover how to get out of sticky situations with Git by reverting past commits, resetting commits from history, locating changes, and reinforcing commits. Finally, explore inner-source culture, which can transform the way you collaborate within an organization—even when the software you’re developing is proprietary.

Learning objectives

• Designing your delivery pipeline
• Enabling continuous integration (CI)
• Adding automated builds
• Making changes based on code reviews
• Adding unit testing
• Adding continuous delivery to your CI pipeline
• Examining commit relationships in Git
• Working with branches in Git
• Reverting changes
• Troubleshooting in Git
• Resolving merge conflicts
• Fine-tuning the GitHub flow
• Adopting an inner-source culture

Lesson 00 – Creating an Action

Lesson 01 – Creating a workflow

Lesson 02 – Adding actions to a workflow

Lesson 03 – Using an action from a repository

Lesson 04 – Developing a CI/CD pipeline with GitHub Actions

Lesson 05 – Building custom actions

Lesson 06 – Publishing an action to the GitHub Marketplace

Recently, Github announced that Github Actions now has support for CI/CD. What this means is that developers can now start using GitHub Actions to create a CI/CD pipeline. In this tutorial, we are going to build a CI/CD pipeline using Github Actions, the pipeline will deploy a react app to Heroku.

Github Action is still in beta, for you to have access to it you need to signup for the beta program. If Actions has been activated on your account you will see the actions tab appear on your repo.

The world’s most popular hosted repository service, GitHub is providing an integrated way to design and develop our workflows by automating the tasks through GitHub Actions.

Workflows are nothing but the steps we follow while bringing an application into production which includes unit testing, integration testing, building artifacts, sanity check, and deploying. In this article, I am going to introduce you to GitHub Actions and show you how to build your workflow to deploy a Machine Learning Application.

If you work in software development teams, you’re probably familiar with the concepts of Continuous Integration (CI) and Continuous Delivery or Continuous Deployment (CD). These practices are commonly combined in a CI/CD pipeline, which is an important part of DevOps. Basically, CI/CD allows you to automatically build, test, and deploy code changes – helping your team work more efficiently.

Continuous integration (CI) involves the test automation of feature branches before they are merged to the main Git branch in a project. This ensures that a codebase does not get updated with changes that could break something. Continuous Delivery (CD), on the other hand, builds upon CI by automating releases of these branches or the main branch. This allows small incremental updates that reach your users faster, in line with Agile software development philosophy.

Continuous integration/continuous delivery (CI/CD) pipelines are the foundation of modern software development, delivering business value in many ways: streamlined releases, software with fewer bugs and automation that removes many time-consuming and error-prone manual steps. You can develop software without CI/CD, but a CI/CD pipeline makes life much easier if your business uses Agile, cloud-native apps or any distributed application architectures such as microservices.

Using the CI/CD strategy in the software development life cycle has many advantages:

1. Standardization of the code production and deployment process, helping to reduce errors and maintain code quality standards.
2. Reduction in time and effort spent on testing and deploying the application manually. The DevOps team can focus on delivering features for the end-users.
3. Ability to run tests on different platforms simultaneously and fix errors quickly
4. Faster shipment of new features faster.

What you’ll learn :

1. How to make a basic deploy pipeline for your code can setup quick, easily and for free.
2. It can run in the cloud whenever someone pushes to your repo. It will warn you when something fails. So in case you forgot to run tests locally or you edited in GitHub UI, you’re covered.
3. GitHub supports a pipeline service called GitHub Actions, covered in this post.
4. We’ll create sample workflow in this post to run a Hello World flow to print a message with a shell command.