Dot Net Programming

The fourth edition of my book is out! You can buy it on Amazon

If you are a an aspiring .NET software architect, or a C# developer wishing to jump into the world of enterprice applications and cloud, this is the right book for you!

Software Architecture with C# 12 and .NET 8 puts high-level design theory to work in a .NET context, teaching you the key skills, technologies, and best practices required to become an effective .NET software architect.

This fourth edition puts emphasis on a case study that will bring your skills to life. You'll learn how to choose between different architectures and technologies at each level of the stack. You'll take an even closer look at Blazor and explore OpenTelemetry for observability, as well as a more practical dive into preparing .NET microservices for Kubernetes integration.

Divided into three parts, this book starts with the fundamentals of software architecture, covering C# best practices, software domains, design patterns, DevOps principles for CI/CD, and more. The second part focuses on the technologies, from choosing data storage in the cloud to implementing frontend microservices and working with Serverless. You'll learn about the main communication technologies used in microservices, such as REST API, gRPC, Azure Service Bus, and RabbitMQ. The final part takes you through a real-world case study where you'll create software architecture for a travel agency.

What’s new in this edition?

Topics are analyzed in greater detail and updated for .NET 8 and the latest Azure components. We have also added a new practical chapter on developing .NET applications for Kubernetes.

Finally, the book has been organized into three parts, creating a flow that will guide you in your journey to becoming a software architect: architectural fundamentals, .NET technologies, and practical coding with a great case study.

Highlights from the World Wide Travel Club case study:

• Code examples in past editions restructured and re-organized into a case study
• Examining user needs and managing requirements with Azure DevOps
• Understanding the application domains and choosing cloud data storage
• Implementing worker microservices with gRPC and RabbitMQ

How does this book differ from other books on C# 12 and .NET 8?

Tags: Kubernetes, Asp.net core, DDD, Entity Framework Core, Microservices, Cloud, Azure

The third edition of my book is out! You can buy it on Amazon

If you are a C# developer wishing to jump into the world of enterprice applications and cloud, this is the right book for you!

From how to collect requirements, and how to master DevOps, selecting the right cloud resources, Web API, front-end frameworks (ASP.Net MVC and Blazor) to microservices design principles and practice,. This new edition updates all subjects to the last cloud and .Net features and adds new chapters:

• A detailed description of gRPC and of how to use it from .NET
• A new chapter that explains in detail how to implement a worker microservice with  ASP.NET + gRPC, and .NET hosted services + RabbitMQ
• An introduction to Artificial Intelligence and Machine Learning
• An introduction to native clients (including a short review of .NET MAUI)

Most of chapters give enough details to cover 90% of all practical applications and give all links and pointers to get more details.The only exceptions are the chapters about artificial intelligence and native clients that are just introductions to big subjects. However,  also there you will find complete learning paths to follow to become an expert.

The first three chapters describe modern development processes, and how to collect and document functional and not-functional requirements. Example of requirement collection and management with Azure DevOps are given.

Then the books moves to the basic cloud concepts and describes how to select the right cloud resources for each application.

Chapter 5 explains the whole therory behind Microservices design, and lists .NET resources that plays a foundamental role in the .NET implementation of Microservices. A self-contained description of Docker, is given, too.

Chapter 6 is dedicated to Kubernetes. There you will find all basic concepts and enough details to cover 90% of all practial applications.

Chapter 7 and 8 are dedicated to data storage and how to interact with them with Entity Framework Core and other clients. There, you will find .the whole theory behind distributed databases, how to maximize read and write parallelism and how to choose between SQL and Not-SQL databases.

Chapter 9 is about serverless and Azure functions. There, you  will find enough details to cover simple-middle complexity functions, and pointers on how to implement more complex functions.

Chapter 10 is dedicated to  the concept of pattern and describes various patterns used throghout the book.

Chapter 11 describes Domain Driven Design, that is the most used design methodology for microservices. Related patterns and their practical usage in .NET layered applications are given, too.

Chapter 12 describes typical patterns of code reusability used in .NET applications.

Chapter 14 gives a detailed description of gRPC and of its usage in .NET applications. Then, a complete implementation of a worker microservice with gRPC and ASP.NET CORE is given. Finally the same example is implemented with a .NET worker service and RabbitMQ.

Further chapters describe SOA architectures  and their implementation with ASP-NET Core (13), ASP.NET Core and ASP.NET Core MVC(15) and Blazor (17).

Chapter 16 puts in practice all concepts learned with ASP.NET Core MVC and Domain Driven Design with the implementation of a front-end microservice.

Chapter 18 is a introduction to native .NET clients that includes also a first look to .NET MAUI. The description is not detailed since a detailed description would require another complete book, but native clients are compared with browser-based clients and frameworks (like Blazor) and complete learning paths are given.

Chapter 19 is an introduction to artificial intelligence and machine learning. The basic principles of the main AI techniques are described, without going deep into the implementation details.Also. the basic theory about machine learning is given. Here the focus is on understanding which problems can be solved with machine learning and how many examples they require. A practical example of supervised learning is given.

Chapter 20 is dedicated to best practices and code metrics.

Chapter 21 and 22 are dedicated to DevOps and to the usage of Azure DevOps and GitHub actions.

Finally chapter 23 is dedicated to testing, test-driven design, unit-tests and functional/acceptance tests.The chapter gives the complete theory and describes in detail xUnit, and Moq.Practical examples of functional tests based on AngleSharp and Selenium are given, too.

DO NOT MISS IT!

Francesco

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