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

Identifying acceptable data loss

In designing systems that must deal with transient failures, data loss will inevitably occur. Many architectural patterns can be layered together to minimize the loss of data, but it is extremely challenging to guarantee that no loss will ever occur.

Later in this chapter, we will examine the implications of data loss and what we can do to compensate for it. Before getting to that, we must identify what acceptable and unacceptable data loss is. The benefit of this is narrowing the scope for unacceptable data loss, to which a high proportion of effort will go towards minimizing this loss.

Acceptable and unacceptable data loss

Defining what acceptable and unacceptable data loss is heavily influenced by the context of the action being performed and the business impact within that context. For example, if adding a customer’s new payment method never succeeds and results in a data loss, it may be reasonable to assume the loss can be recovered...