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

Instrumenting the producer

The producer is the component responsible for publishing messages to a broker. The publishing process itself is usually synchronous: we send a request to the broker and get a response from it indicating whether the message was published successfully.

Depending on the messaging system and producer needs, one publish request may carry one or more messages. We’ll discuss batching in the Instrumenting batching scenarios section. For now, let’s focus on a single message case.

To trace it, we need to make sure we create an activity when we publish a message, so we can track the call duration and status and debug individual requests. We’d also be interested in metrics for duration, throughput, and failure rate – it’s important to budget cloud messaging solutions or scale self-hosted brokers.

Another essential part of producer instrumentation is context propagation. Let’s stop here for a second and discuss it.

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