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 consumer

While you might be able to get away without custom instrumentation on the producer, consumer instrumentation is unavoidable.

Some brokers push messages to consumers using synchronous HTTP or RPC calls, and the existing framework instrumentation can provide the bare minimum of observability data. In all other cases, messaging traces and metrics are all we have to detect consumer health and debug issues.

Let’s start by tracing individual messages – recording when they arrive in the consumer and how they are processed. This allows us to debug issues by answering questions such as “Where is this message now?” or “Why did it take so long to process the data?”

Tracing consumer operations

When using Azure Queue Storage, applications request one or more messages from the queue. Received messages stay in the queue but become invisible to other consumers for configurable visibility timeout. The application processes...