You're reading from Continuous Testing, Quality, Security, and Feedback Essential strategies and secure practices for DevOps, DevSecOps, and SRE transformations

Product type Paperback

Published in Sep 2024

Publisher Packt

ISBN-13 9781835462249

Length 350 pages

Edition 1st Edition

Languages

Python

Tools

Selenium

Concepts

Design

Author (1):

Marc Hornbeek

View More author details

Table of Contents (22) Chapters

Preface

1. Part 1: Understanding Continuous Testing, Quality, Security, and Feedback FREE CHAPTER

2. Chapter 1: Principles of Continuous Testing, Quality, Security, and Feedback

3. Chapter 2: The Importance of Continuous Testing, Quality, Security, and Feedback

4. Chapter 3: Experiences and Pitfalls with Continuous Testing, Quality, Security, and Feedback

5. Part 2: Determining Solutions Priorities

6. Chapter 4: Engineering Approach to Continuous Testing, Quality, Security, and Feedback

7. Chapter 5: Determining Transformation Goals

8. Chapter 6: Discovery and Benchmarking

9. Chapter 7: Selecting Tool Platforms and Tools

10. Chapter 8: Applying AL/ML to Continuous Testing, Quality, Security, and Feedback

11. Part 3: Deep Dive into Roadmaps, Implementation Patterns, and Measurements

12. Chapter 9: Use Cases for Integrating with DevOps, DevSecOps, and SRE

13. Chapter 10: Building Roadmaps for Implementation

14. Chapter 11: Understanding Transformation Implementation Patterns

15. Chapter 12: Measuring Progress and Outcomes

16. Part 4: Exploring Future Trends and Continuous Learning

17. Chapter 13: Emerging Trends

18. Chapter 14: Exploring Continuous Learning and Improvement

19. Glossary and References

20. Index

Why subscribe?

21. Other Books You May Enjoy

How generative AI can be used to accelerate discovery and benchmarking

Generative AI can significantly enhance the efficiency and quality of current state discovery, benchmarking gap assessments, and the creation of CSVSM in several impactful ways:

Automated data collection and analysis:
- Efficiency: Generative AI can automate the collection of data across various systems and tools used in the current state processes. By parsing through logs, project management tools, and development environments, AI can quickly gather necessary information, reducing manual effort and time.
- Quality: AI algorithms can analyze this data more accurately and consistently than manual methods, identifying patterns, bottlenecks, and inefficiencies that might not be evident to human analysts.
Enhanced visualization of value streams:
- Efficiency: AI can automatically generate visual representations of value streams based on the collected data. This automation speeds up the creation of CSVSMs, allowing...