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

Resource usage attribution


In this last example, we will discuss a technique that is not, strictly speaking, a functionality commonly provided by distributed tracing systems, but rather a side effect of the distributed context propagation mechanism that underlies all tracing instrumentation and can be relied upon in applications instrumented for tracing. We saw an example of this earlier when we discussed an implicit propagation of the frontend request ID used to tag transactions that were blocking in a mutex queue. In this section, we will discuss the use of metadata propagation for resource usage attribution.

Resource usage attribution is an important function in large organizations, especially for capacity planning and efficiency improvements. We can define it as a process of measuring the usage of some resource, such as CPU cores, or disk space, and attributing it to some higher-level business parameter, such as a product or a business line. For example, consider a company that has two...