Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Multi-Cloud Strategy for Cloud Architects

You're reading from   Multi-Cloud Strategy for Cloud Architects Learn how to adopt and manage public clouds by leveraging BaseOps, FinOps, and DevSecOps

Arrow left icon
Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781804616734
Length 470 pages
Edition 2nd Edition
Tools
Arrow right icon
Author (1):
Arrow left icon
Jeroen Mulder Jeroen Mulder
Author Profile Icon Jeroen Mulder
Jeroen Mulder
Arrow right icon
View More author details
Toc

Table of Contents (23) Chapters Close

Preface 1. Introduction to Multi-Cloud FREE CHAPTER 2. Collecting Business Requirements 3. Starting the Multi-Cloud Journey 4. Service Designs for Multi-Cloud 5. Managing the Enterprise Cloud Architecture 6. Controlling the Foundation Using Well-Architected Frameworks 7. Designing Applications for Multi-Cloud 8. Creating a Foundation for Data Platforms 9. Creating a Foundation for IoT 10. Managing Costs with FinOps 11. Maturing FinOps 12. Cost Modeling in the Cloud 13. Implementing DevSecOps 14. Defining Security Policies 15. Implementing Identity and Access Management 16. Defining Security Policies for Data 17. Implementing and Integrating Security Monitoring 18. Developing for Multi-Cloud with DevOps and DevSecOps 19. Introducing AIOps and GreenOps in Multi-Cloud 20. Conclusion: The Future of Multi-Cloud 21. Other Books You May Enjoy
22. Index

Summary

AIOps was a new kid on the block but, since 2020, it has emerged as an almost essential platform for managing complex cloud environments. AIOps systems help organizations in detecting changes and anomalies in their IT environments and already predicting what impact these events might have on other components within their environments. AIOps systems can even predict this from planned changes coming from DevOps systems such as CI/CD pipelines. To be able to do that, AIOps makes use of big data analysis: it has access to a lot of different data sources, inside and outside IT environments. This data is analyzed and fed into algorithms: this is where AI comes in, and ML. AIOps systems learn so that they can actually predict future events.

AIOps are complex systems that require vast investments from vendors, and thus from companies that want to start working with AIOps. However, most organizations want to become more and more data-driven, meaning that data is driving all decisions...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime