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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 previous chapters, we explored telemetry auto-collection, and now we have learned how to customize this telemetry. We learned about different sampling approaches – head-based and tail-based. Head-based sampling makes the decision to record a trace (or span) when it starts with a certain probability. Children can follow parent decisions and then traces are always complete, but it’s not possible to control the volume of traces on individual services. To overcome this, downstream services can configure different rates and use consistent sampling to maximize the number of complete traces. Some traces become partial but are still useful for monitoring individual services or groups of them.

Probability sampling captures a percentage of all traces and is great to mitigate performance overhead. If you need predictable costs, you should consider rate-based sampling. It’s implemented in the OpenTelemetry Collector or by observability vendors. The OpenTelemetry...

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