Book Image

Modern Distributed Tracing in .NET

By : Liudmila Molkova
Book Image

Modern Distributed Tracing in .NET

By: Liudmila Molkova

Overview of this book

As distributed systems become more complex and dynamic, their observability needs to grow to aid the development of holistic solutions for performance or usage analysis and debugging. Distributed tracing brings structure, correlation, causation, and consistency to your telemetry, thus allowing you to answer arbitrary questions about your system and creating a foundation for observability vendors to build visualizations and analytics. Modern Distributed Tracing in .NET is your comprehensive guide to observability that focuses on tracing and performance analysis using a combination of telemetry signals and diagnostic tools. You'll begin by learning how to instrument your apps automatically as well as manually in a vendor-neutral way. Next, you’ll explore how to produce useful traces and metrics for typical cloud patterns and get insights into your system and investigate functional, configurational, and performance issues. The book is filled with instrumentation examples that help you grasp how to enrich auto-generated telemetry or produce your own to get the level of detail your system needs, along with controlling your costs with sampling, aggregation, and verbosity. By the end of this book, you'll be ready to adopt and leverage tracing and other observability signals and tools and tailor them to your needs as your system evolves.
Table of Contents (23 chapters)
1
Part 1: Introducing Distributed Tracing
6
Part 2: Instrumenting .NET Applications
11
Part 3: Observability for Common Cloud Scenarios
16
Part 4: Implementing Distributed Tracing in Your Organization

Choosing the right signal

When we discussed individual telemetry signals in Chapters 6 to 8, we provided suggestions on when to use each of them. Let’s do a quick recap:

  • Distributed traces describe individual network calls and other interesting operations in detail. Spans have causal relationships, allowing us to understand the request flow in distributed systems.

Traces document the request flow through the system and are essential for investigating errors or outliers in the long tail of latency distribution. Traces provide means to correlate other telemetry signals.

  • Metrics collect aggregated data with low-cardinality attributes and provide a low-resolution view of the overall system state. They help optimize telemetry collection and reduce storage costs and query time.
  • Events provide highly structured information about individual occurrences of important things. The key difference between spans and events is that spans have unique contexts and describe...