Book Image

Mastering Distributed Tracing

By : Yuri Shkuro
Book Image

Mastering Distributed Tracing

By: Yuri Shkuro

Overview of this book

Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable. Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems.
Table of Contents (21 chapters)
Mastering Distributed Tracing
Contributors
Preface
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15
Afterword
Index

Integration with metrics


There are two types of integrations we are going to review: emitting metrics via tracing instrumentation and partitioning metrics by the request metadata attributes.

Standard metrics via tracing instrumentation

In this section, we will discuss integration with metrics that is somewhat unique to the OpenTracing API. Since OpenTracing is a pure API that describes distributed transactions, without default implementations, it can be implemented to generate data that is unrelated to tracing. Specifically, if we think about a typical metrics instrumentation for an RPC service, we will see that the tracing instrumentation already collects all the same signals as advocated by the RED (Rate, Error, Duration) method [5]:

  • We start a server span for every inbound request, therefore we can count how many requests our service receives, that is, its throughput or request rate (R in RED).

  • If the request encounters an error, the tracing instrumentation sets the error=true tag on the...