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

Correlation and causation

Correlation identifiers have been critical to monolithic application logging for as long as I can remember. This involves generating a unique identifier, which is then passed from function to function and included in any log outputs. That way, you can query lots of log entries using a single common identifier to correlate them together. This forms a trace within the logs so that you can observe a connected pattern of messaging from within the application code.

As we shift to microservices, this challenge goes beyond a single application process. Most commonly, correlation identifiers are propagated from one service to the next using HTTP for correlation.

When we move to event-driven architecture, we introduce a few new challenges to this correlation pattern.

Correlation identifiers need to persist across events by being included in the event message from the producer. Then, any consumer can reuse the correlation identifier in its own log output.

...