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

Head-based consistent sampling


Head-based consistent sampling, also known as upfront sampling, makes the sampling decision once per trace at the beginning of the trace. The decision is usually made by the tracing libraries running inside the application, because consulting the tracing backend at the point of creating the first span would put the tracing infrastructure onto the critical path of the business requests, which is highly undesirable for performance and reliability reasons.

The decision is recorded as part of the trace metadata and propagated throughout the call graph as part of the context. This sampling scheme is consistent because it ensures that either all spans of a given trace are captured by the tracing system or none of them are. Head-based sampling is employed by the majority of existing industrial-grade tracing systems today.

When the sampling decision must be made at the root of the trace, there is relatively little information available to the tracer on which to base...