Book Image

Implementing Event-Driven Microservices Architecture in .NET 7

By : Joshua Garverick, Omar Dean McIver
4 (1)
Book Image

Implementing Event-Driven Microservices Architecture in .NET 7

4 (1)
By: Joshua Garverick, Omar Dean McIver

Overview of this book

This book will guide you through various hands-on practical examples for implementing event-driven microservices architecture using C# 11 and .NET 7. It has been divided into three distinct sections, each focusing on different aspects of this implementation. The first section will cover the new features of .NET 7 that will make developing applications using EDA patterns easier, the sample application that will be used throughout the book, and how the core tenets of domain-driven design (DDD) are implemented in .NET 7. The second section will review the various components of a local environment setup, the containerization of code, testing, deployment, and the observability of microservices using an EDA approach. The third section will guide you through the need for scalability and service resilience within the application, along with implementation details related to elastic and autoscale components. You’ll also cover how proper telemetry helps to automatically drive scaling events. In addition, the topic of observability is revisited using examples of service discovery and microservice inventories. By the end of this book, you’ll be able to identify and catalog domains, events, and bounded contexts to be used for the design and development of a resilient microservices architecture.
Table of Contents (21 chapters)
1
Part 1:Event-Driven Architecture and .NET 7
6
Part 2:Testing and Deploying Microservices
12
Part 3:Testing and Deploying Microservices

Minimizing Data Loss

In this chapter, we will look at techniques for minimizing or eliminating data loss. Cloud-native development architectures bring an inherent risk of data loss through transient failures in separate services and/or connectivity between them. As such, we design applications for that failure, and event-driven architecture uses some key techniques to mitigate this risk of loss. We will explore paradigms, such as eventual consistency and guaranteed delivery, and learn how to contextually identify data that may be susceptible to loss, along with defining how much loss, if any, is acceptable.

In this chapter, we will cover the following key topics:

  • Learn more about typical data consistency paradigms, such as immediate consistency and eventual consistency
  • Learn how to identify and plan for potential data loss, including acceptable levels of loss and mitigation strategies
  • For situations that require zero data loss, learn how to implement techniques that...