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Continuous Testing, Quality, Security, and Feedback

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

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835462249
Length 350 pages
Edition 1st Edition
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Author (1):
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Marc Hornbeek Marc Hornbeek
Author Profile Icon Marc Hornbeek
Marc Hornbeek
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Table of Contents (22) Chapters Close

Preface 1. Part 1: Understanding Continuous Testing, Quality, Security, and Feedback
2. Chapter 1: Principles of Continuous Testing, Quality, Security, and Feedback FREE CHAPTER 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 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...
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