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Modern Distributed Tracing in .NET

You're reading from   Modern Distributed Tracing in .NET A practical guide to observability and performance analysis for microservices

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781837636136
Length 336 pages
Edition 1st Edition
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Author (1):
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Liudmila Molkova Liudmila Molkova
Author Profile Icon Liudmila Molkova
Liudmila Molkova
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Introducing Distributed Tracing
2. Chapter 1: Observability Needs of Modern Applications FREE CHAPTER 3. Chapter 2: Native Monitoring in .NET 4. Chapter 3: The .NET Observability Ecosystem 5. Chapter 4: Low-Level Performance Analysis with Diagnostic Tools 6. Part 2: Instrumenting .NET Applications
7. Chapter 5: Configuration and Control Plane 8. Chapter 6: Tracing Your Code 9. Chapter 7: Adding Custom Metrics 10. Chapter 8: Writing Structured and Correlated Logs 11. Part 3: Observability for Common Cloud Scenarios
12. Chapter 9: Best Practices 13. Chapter 10: Tracing Network Calls 14. Chapter 11: Instrumenting Messaging Scenarios 15. Chapter 12: Instrumenting Database Calls 16. Part 4: Implementing Distributed Tracing in Your Organization
17. Chapter 13: Driving Change 18. Chapter 14: Creating Your Own Conventions 19. Chapter 15: Instrumenting Brownfield Applications 20. Assessments 21. Index 22. Other Books You May Enjoy

Summary

In this chapter, we explored metrics in .NET and OpenTelemetry.

Metrics allow us to collect aggregated multi-dimensional data. They produce unbiased telemetry with a predictable volume at any scale and allow us to monitor system health, performance, and usage.

Metrics can’t have high-cardinality attributes, so we can’t use them to detect problems that happen in specific and narrow cases – for this, we need distributed tracing or events. .NET provides an OpenTelemetry metrics implementation that consists of the Meter class, which can create specific instruments: counters, gauges, and histograms.

Counters are used to report additive values and can be synchronous or asynchronous. Gauges report current, non-additive values asynchronously, while histograms report value distribution.

With this, you should be able to identify scenarios where metrics are beneficial, choose appropriate instruments, and efficiently report metrics in your application....

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