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Enterprise DevOps for Architects

You're reading from  Enterprise DevOps for Architects

Product type Book
Published in Nov 2021
Publisher Packt
ISBN-13 9781801812153
Pages 288 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Jeroen Mulder Jeroen Mulder
Profile icon Jeroen Mulder

Table of Contents (21) Chapters

Preface 1. Section 1: Architecting DevOps for Enterprises
2. Chapter 1: Defining the Reference Architecture for Enterprise DevOps 3. Chapter 2: Managing DevOps from Architecture 4. Chapter 3: Architecting for DevOps Quality 5. Chapter 4: Scaling DevOps 6. Chapter 5: Architecting Next-Level DevOps with SRE 7. Section 2: Creating the Shift Left with AIOps
8. Chapter 6: Defining Operations in Architecture 9. Chapter 7: Understanding the Impact of AI on DevOps 10. Chapter 8: Architecting AIOps 11. Chapter 9: Integrating AIOps in DevOps 12. Chapter 10: Making the Final Step to NoOps 13. Section 3: Bridging Security with DevSecOps
14. Chapter 11: Understanding Security in DevOps 15. Chapter 12: Architecting for DevSecOps 16. Chapter 13: Working with DevSecOps Using Industry Security Frameworks 17. Chapter 14: Integrating DevSecOps with DevOps 18. Chapter 15: Implementing Zero Trust Architecture 19. Assessments 20. Other Books You May Enjoy

Defining the roadmap to NoOps

NoOps is not a leap of faith. As with DevOps and AIOps, any next step requires a plan and a roadmap. Using the principles of heuristic automation and AIOps, we can leverage automation for intelligent automation, collaborating with cloud-native automation, and automated application deployment in CI/CD pipelines.

The following figure shows how NoOps consists of three major components. These three components are the roadmap to get to a level of automation where dedicated operations are no longer required. DevOps teams are end-to-end responsible for the development, deployment, running, and maintenance of the code, supported by fully automated processes and AI:

Figure 10.3 – Components of NoOps

The end state is predictive automation using predictive analytics that analyzes current data to eventually make predictions for the future. It includes the following:

  • Scaling for future needs, for instance by analyzing...
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