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 batching scenarios

Instrumentation for batching scenarios can be different depending on the use case – transport-level batching needs a slightly different approach compared to batch processing.

Batching on a transport level

Messages can be batched together to minimize the number of network calls. It can be used by producers or consumers, and systems such as Kafka, Amazon SQS, or Azure Service Bus support batching on both sides.

On the consumer, when multiple messages are received together but processed independently, everything we had for single message processing still applies.

From a tracing perspective, the only thing we’d want to change is to add attributes that record all received message identifiers and batch size on the outer iteration activity.

From the metrics side, we’d also want to measure individual message processing duration, error rate, and throughput. We can track them all by adding a message processing duration histogram...