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

Observability

It would be prudent to start with a clear definition of observability. In other words, it means to be able to notice or discern something. Applied to our focus on software applications, we can be more specific about what we are discern and how we do so: to be able to measure the internal state of a system by its outputs.

In software systems, this is achieved through the enablement of what is commonly referred to as the three pillars of observability:

  1. Metrics: A series of measurements over time
  2. Logs: A record of messages describing noticeable events within a system
  3. Traces: A set of indicators throughout logs that connect a series of related events

At this point, it is worth addressing the critical commentary you will find on the three pillars of observability in more recent online publications. There are indeed some shortcomings of these pillars at a hyper-scale, and thought leaders are evolving beyond them to refine the quality and accuracy of...