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

Summary


This chapter introduced a demo application, HotROD, that is instrumented for distributed tracing, and by tracing that application with Jaeger, an open source distributed tracing system, demonstrated the following features common to most end-to-end tracing systems:

  • Distributed transaction monitoring: Jaeger records the execution of individual requests across the whole stack of microservices, and presents them as traces.

  • Performance and latency optimization: Traces provide very simple visual guides to performance issues in the application. The practitioners of distributed tracing often say that fixing the performance issue is the easy part, but finding it is the hard part.

  • Root cause analysis: The highly contextualized nature of the information presented in the traces allows for quickly narrowing down to the parts of the execution that are responsible for issues with the execution (for example, the timeouts when calling Redis, or the mutex queue blocking).

  • Service dependency analysis...