You're reading from Tools and Skills for .NET 8 Get the career you want with good practices and patterns to design, debug, and test your solutions 

Product type Paperback

Published in Jul 2024

Publisher Packt

ISBN-13 9781837635207

Length 778 pages

Edition 1st Edition

Languages

Tools

.NET

Concepts

Cloud Native

Author (1):

Mark J. Price

View More author details

Table of Contents (22) Chapters

Preface

1. Introducing Tools and Skills for .NET

2. Making the Most of the Tools in Your Code Editor FREE CHAPTER

3. Source Code Management Using Git

4. Debugging and Memory Troubleshooting

5. Logging, Tracing, and Metrics for Observability

6. Documenting Your Code, APIs, and Services

7. Observing and Modifying Code Execution Dynamically

8. Protecting Data and Apps Using Cryptography

9. Building an LLM-Based Chat Service

10. Dependency Injection, Containers, and Service Lifetime

11. Unit Testing and Mocking

12. Integration and Security Testing

13. Benchmarking Performance, Load, and Stress Testing

14. Functional and End-to-End Testing of Websites and Services

15. Containerization Using Docker

16. Cloud-Native Development Using .NET Aspire

17. Design Patterns and Principles

18. Software and Solution Architecture Foundations

19. Your Career, Teamwork, and Interviews

20. Epilogue

21. Index

Using Semantic Kernel with an OpenAI model

The AI experts who build LLMs tend to use Linux as their operating system and Python for programming. Tutorials and documentation tend to assume developers will use those platforms, too. Using another programming language or framework that’s not natively designed for .NET, and dealing with cross-language or cross-framework issues can introduce complexity and reduce the maintainability of your project.

Understanding Semantic Kernel

Semantic Kernel is designed with the .NET ecosystem in mind, providing integration with C# and other .NET languages. This means it’s naturally easier to work with from a .NET developer’s perspective, offering libraries or packages that are idiomatic to C# developers.

Semantic Kernel can leverage the asynchronous programming model of .NET to handle input/output (I/O)-bound tasks more efficiently, which is crucial when integrating network-bound services like an LLM API. This results...