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Automating DevOps with GitLab CI/CD Pipelines

You're reading from  Automating DevOps with GitLab CI/CD Pipelines

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781803233000
Pages 348 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
Christopher Cowell Christopher Cowell
Profile icon Christopher Cowell
Nicholas Lotz Nicholas Lotz
Profile icon Nicholas Lotz
Chris Timberlake Chris Timberlake
Profile icon Chris Timberlake
View More author details

Table of Contents (18) Chapters

Preface 1. Part 1 Getting Started with DevOps, Git, and GitLab
2. Chapter 1: Understanding Life Before DevOps 3. Chapter 2: Practicing Basic Git Commands 4. Chapter 3: Understanding GitLab Components 5. Chapter 4: Understanding GitLab’s CI/CD Pipeline Structure 6. Part 2 Automating DevOps Stages with GitLab CI/CD Pipelines
7. Chapter 5: Installing and Configuring GitLab Runners 8. Chapter 6: Verifying Your Code 9. Chapter 7: Securing Your Code 10. Chapter 8: Packaging and Deploying Code 11. Part 3 Next Steps for Improving Your Applications with GitLab
12. Chapter 9: Enhancing the Speed and Maintainability of CI/CD Pipelines 13. Chapter 10: Extending the Reach of CI/CD Pipelines 14. Chapter 11: End-to-End Example 15. Chapter 12: Troubleshooting and the Road Ahead with GitLab 16. Index 17. Other Books You May Enjoy

Building code in a CI/CD pipeline

At the risk of oversimplifying some of the mechanics that happen behind the scenes when you run software, we can generally think of interpreted computer languages such as Python or Ruby as executing raw source code, whereas compiled languages such as Java, C, or C# must convert that source code into a runnable form by compiling it, and then execute the compiled version of the program.

This is an important distinction to keep in mind when configuring a pipeline to verify your code because it means that if your project contains any code written in a compiled language (even if it’s only a small portion of your overall project), you probably need to include a build job in your pipeline before any verification jobs take place. We say probably because some of the jobs that typically run during the verification stage of a pipeline (for example, Code Quality) look directly at source code, whereas others interact with code as it runs. So, if your...

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