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

Chapter 8. All About Sampling

The gathering of monitoring data in production is always a compromise between the costs, in terms of storage and performance overhead, and the expressiveness of the collected data. The more data we collect, the better we hope to be able to diagnose the situation, should something go wrong, yet we don't want to slow down the applications or pay exorbitant bills for storage. Even though most logging frameworks support multiple levels of log severity, a common wisdom is to tune the loggers in production to discard anything logged with the debug level or lower. Many organizations even adopt the rule that successful requests should leave no logs at all, and you only log when there is some issue with the request.

Distributed tracing is not immune to this compromise either. Depending on the verbosity of the instrumentation, tracing data can easily exceed the volume of the actual business traffic sustained by an application. Collecting all that data in memory, and sending...