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

Observability via a service mesh


If we place a service mesh in the path of every network request between the services in an application, it makes it an ideal place to collect consistent, standardized telemetry about the application. This standardized observability alone may be enough to compensate for a small performance loss introduced by going through a proxy for every request because it dramatically enhances the operational properties of the system, making it easier to monitor and troubleshoot:

  • The sidecar can emit uniformly named metrics about the traffic going in and out of a service instance, such as throughput, latency, and error rates (also known as the RED method (Rate, Error, Duration). These metrics can be used to monitor the health of the services and for creating standardized dashboards.

  • The sidecar can produce rich access logs. Sometimes these logs need to be produced and stored securely for compliance reasons. Having a single logical component responsible for all those logs...