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Implementing Event-Driven Microservices Architecture in .NET 7

You're reading from   Implementing Event-Driven Microservices Architecture in .NET 7 Develop event-based distributed apps that can scale with ever-changing business demands using C# 11 and .NET 7

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781803232782
Length 326 pages
Edition 1st Edition
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Joshua Garverick Joshua Garverick
Author Profile Icon Joshua Garverick
Joshua Garverick
Omar Dean McIver Omar Dean McIver
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Omar Dean McIver
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Table of Contents (21) Chapters Close

Preface 1. Part 1:Event-Driven Architecture and .NET 7
2. Chapter 1: The Sample Application FREE CHAPTER 3. Chapter 2: The Producer-Consumer Pattern 4. Chapter 3: Message Brokers 5. Chapter 4: Domain Model and Asynchronous Events 6. Part 2:Testing and Deploying Microservices
7. Chapter 5: Containerization and Local Environment Setup 8. Chapter 6: Localized Testing and Debugging of Microservices 9. Chapter 7: Microservice Observability 10. Chapter 8: CI/CD Pipelines and Integrated Testing 11. Chapter 9: Fault Injection and Chaos Testing 12. Part 3:Testing and Deploying Microservices
13. Chapter 10: Modern Design Patterns for Scalability 14. Chapter 11: Minimizing Data Loss 15. Chapter 12: Service and Application Resiliency 16. Chapter 13: Telemetry Capture and Integration 17. Chapter 14: Observability Revisited 18. Assessments 19. Index 20. Other Books You May Enjoy

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...

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