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

Aggregation of logs

When using Kubernetes, we can think of two primary methods for emitting logs. The first is directly from our code to an external logging system. The second is direct output via the standard output and error streams.

To aggregate logs directly to an external logging system, we can use Azure Application Insights. It can natively instrument .NET applications (among many other supported languages) with a few code changes.

To aggregate logs written to the standard output and error streams, we can use Container Insights, which is a capability within Azure Monitor. Container Insights is a great utility for viewing and querying logs produced by multiple Kubernetes clusters, but it currently does not easily support the level of structured interrelationship logging that this application will generate.

The MTAEDA application will use telemetry and logging directly to Application Insights so that we can support tracing.

Now, let us set up an Applications Insight...