You're reading from Software Architecture with C# 10 and .NET 6 – Third Edition Develop software solutions using microservices, DevOps, EF Core, and design patterns for Azure

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781803235257

Length 714 pages

Edition 3rd Edition

Languages

Tools

.NET

Concepts

Design Patterns

Authors (2):

Francesco Abbruzzese

Gabriel Baptista

View More author details

Table of Contents (27) Chapters

Preface

1. Understanding the Importance of Software Architecture FREE CHAPTER

2. Non-Functional Requirements

3. Documenting Requirements with Azure DevOps

4. Deciding on the Best Cloud-Based Solution

5. Applying a Microservice Architecture to Your Enterprise Application

6. Azure Kubernetes Service

7. Interacting with Data in C# – Entity Framework Core

8. How to Choose Your Data Storage in the Cloud

9. Working with Azure Functions

10. Design Patterns and .NET 6 Implementation

11. Understanding the Different Domains in Software Solutions

12. Implementing Code Reusability in C# 10

13. Applying Service-Oriented Architectures with .NET

14. Implementing Microservices with .NET

15. Presenting ASP.NET Core MVC

16. Implementing Frontend Microservices with ASP.NET Core

17. Blazor WebAssembly

18. Native versus Web Clients

19. Artificial Intelligence and Machine Learning

20. Best Practices in Coding C# 10

21. Understanding DevOps Principles

22. Challenges of Applying CI & CD Scenarios

23. Testing Your Enterprise Application

24. Answers

25. Other Books You May Enjoy

26. Index

From theory to practice: the role of a software architect in an ML project

After this short description of the main techniques used in artificial intelligence and the basic principles behind machine learning, it is time to understand how you, as a software architect, will act in projects where ML is essential to deliver the best solution for your customer.

Today it is common to hear from customers their desire to deliver a solution where AI is included. As you could see in the sections above, there is no way to do so without data. Machine learning is not magic, and to have a good solution, you must apply science. This is one of the first messages you must transmit to your team as a software architect – there is no ML without planning the way you will have the data needed to achieve the goal of the required prediction. The next subsections will describe the steps needed to deliver a machine learning solution.