GitHub CI/CD: A Practical Tutorial for Setting Up Your github Pipeline

In this blog, I will guide you on the power of CI/CD in GitHub with a step-by-step guide. Learn to set up automated workflows, boost project efficiency, and streamline development processes for better code quality and faster deployments.

Certainly! It seems that I've encountered a challenge in my current development workflow when deploying minor code changes. The existing process involves manually publishing code from Visual Studio, creating backups of the current code on the server, and then replacing it with the new code. To address this, it's advisable to transition to an automated solution utilizing a Continuous Integration/Continuous Deployment (CI/CD) pipeline. 

By implementing a CI/CD pipeline, you can streamline and automate the deployment process, making it more efficient and reducing the risk of manual errors. The CI/CD pipeline will handle tasks such as code compilation, testing, and deployment automatically, ensuring that the latest changes are seamlessly deployed to the desired environment. 

This transition will not only save time but also enhance the reliability of your deployment process, allowing your team to focus more on development and less on manual deployment tasks. 

For additional information, refer to the steps outlined below for guidance.  

Step 1: 

Go to your repository and click on the Actions tab

Step 2: 

Now, Select the workflow according to your development. Here I am using .NET workflow.  

Step 3: 

Now you can see the default pipeline as below.

In that, you can change your branch as per your requirement.

Step 4: 

You can now incorporate three new sections as outlined below to build the code and publish the folder as an artifact. 

Upon integrating this code, your YAML file will now appear as follows. 

In the code above, you have the flexibility to rename the zip file or the publish folder according to your preferences. 

1. Build and Publish : This step is responsible for building and publishing the code. 

• Commands: 

• dotnet restore: Restores the project's dependencies. 

• dotnet build: Compiles the project. 

• dotnet publish -o publish: Publishes the project output to the 'publish' folder. 
   

2. Zip Output : This step involves compressing the contents of the 'publish' folder into a zip file. 

• Commands: 

• cd publish: Changes the working directory to the 'publish' folder. 

• zip -r ../output .: Creates a zip file named 'output' containing the contents of the 'publish' folder. 
   

3. Upload Zip Archive :This step uploads the zip archive to the workflow run as an artifact. 

• Using: The actions/upload-artifact@v2 GitHub Action. 

• Configuration: 

• name: test: Specifies the name of the artifact as 'test'. 

• path: ./publish: Indicates the path of the folder to be archived and uploaded. 

By using the given code, you receive a finalized published folder prepared for deployment on the server. However, the deployment process on the server requires manual intervention. 

To access the published folder, navigate to the "Actions" tab. Click on the "test" workflow, and you can download the published folder from there. 

Step 5: 

In the steps mentioned above, you previously followed a manual process, but now you have transitioned to an automatic process. 

To automate the process, you'll need to install a self-hosted runner on the virtual machine where your application is hosted. 

What is Self-hosted runner? 

self-hosted runner is a system that you deploy and manage to execute jobs from GitHub Actions on GitHub.com. 

To install the self-hosted runner, follow the basic steps. 

1. Under your repository name, click Settings. If you cannot see the "Settings" tab, select the dropdown menu, then click Settings.
2. In the left sidebar, click Actions, then click Runners and then click on New self-hosted runner. 
   

3. Select the operating system image and architecture of your self-hosted runner machine. 

4. Open a shell on your self-hosted runner machine and run each shell command in the order shown.
   

For more details you can visit https://docs.github.com/en/enterprise-cloud@latest/actions/hosting-your-own-runners/managing-self-hosted-runners/adding-self-hosted-runners 

Step 6: 

To automate the process, you can remove the last two sections, "Zip Output" and "Upload Zip Archive," and replace them with the following code. 

1. Backup & Deploy : This step is responsible for creating a backup, making necessary modifications, and deploying the application.

• Commands: 

• $datestamp = Get-Date -Format "yyyyMMddHHmmss": Retrieves the current date and time in the specified format. 

• cd publish: Changes the working directory to the 'publish' folder. 

• Remove-Item web.config: Deletes the 'web.config' file. 

• Remove-Item appsettings.json: Deletes the 'appsettings.json' file. 

• Remove-Item appsettings.Development.json: Deletes the 'appsettings.Development.json' file. 

• Stop-WebSite 'DemoGitHubPipeline': Stops the website with the specified name. 

• Compress-Archive D:\Published\DemoGitHubPipeline D:\Published\Backup\Backup_$datestamp.zip: Creates a compressed archive (zip) of the existing deployment with proper timestamp. 

• Copy-Item * D:\Published\DemoGitHubPipeline -Recurse -Force: Copies all contents from the 'publish' folder to the deployment directory. 

• Start-WebSite 'DemoGitHubPipeline': Restarts the website with the specified name. 

Note: 

• Ensure that the paths and folder structures match the actual locations in your setup. 

• Adjust the website name and paths based on your specific configuration. 

Conclusion:

In summary, implementing a CI/CD pipeline in GitHub is a pivotal step towards achieving efficiency, reliability, and accelerated development cycles. The integration of CI/CD streamlines the software delivery process by automating testing, building, and deployment, leading to consistent and high-quality releases. 

GitHub Actions, with its native CI/CD capabilities, provides a powerful and flexible platform for orchestrating workflows. Leveraging its features, development teams can not only automate repetitive tasks but also ensure rapid feedback on code changes, enabling early detection of issues and facilitating collaboration.