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Learning Continuous Integration with Jenkins

You're reading from   Learning Continuous Integration with Jenkins An end-to-end guide to creating operational, secure, resilient, and cost-effective CI/CD processes

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781835087732
Length 396 pages
Edition 3rd Edition
Tools
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Author (1):
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Nikhil Pathania Nikhil Pathania
Author Profile Icon Nikhil Pathania
Nikhil Pathania
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1: The Concepts FREE CHAPTER
2. Chapter 1: The What, How, and Why of Continuous Integration 3. Part 2: Engineering the CI Ecosystem
4. Chapter 2: Planning, Deploying, and Maintaining Jenkins 5. Chapter 3: Securing Jenkins 6. Chapter 4: Extending Jenkins 7. Chapter 5: Scaling Jenkins 8. Part 3: Crafting the CI Pipeline
9. Chapter 6: Enhancing Jenkins Pipeline Vocabulary 10. Chapter 7: Crafting AI-Powered Pipeline Code 11. Chapter 8: Setting the Stage for Writing Your First CI Pipeline 12. Chapter 9: Writing Your First CI Pipeline 13. Part 4: Crafting the CD Pipeline
14. Chapter 10: Planning for Continuous Deployment 15. Chapter 11: Writing Your First CD Pipeline 16. Chapter 12: Enhancing Your CI/CD Pipelines 17. Index 18. Other Books You May Enjoy

Crafting AI-Powered Pipeline Code

In the preceding chapter, we delved deep into Jenkins’ Declarative Pipeline syntax, arming ourselves with a comprehensive vocabulary. This was not just an exercise in familiarization but a strategic move to prepare ourselves well for the current chapter. By grasping the nuances of the syntax, we’ve paved the way for the integration of an exciting collaborator in our coding journey: artificial intelligence.

The realm of AI is vast and diverse, and among its stellar achievements is ChatGPT, a product of OpenAI’s groundbreaking research. This model stands out for its ability to understand, process, and produce human-like text. When combined with our Jenkins expertise, ChatGPT becomes a potent ally, making the task of crafting pipeline code not just simpler but also innovative.

Effective collaboration with ChatGPT requires a systematic approach. Therefore, the current chapter introduces the Describe > Run > Troubleshoot...

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