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

Service graphs


You have seen examples of the service graphs in previous chapters, some generated by Jaeger, and others generated by the service mesh Istio. There are other open source tools, such as Weaveworks Scope [2] and Kiali [3], that can provide similar service graphs by integrating with other infrastructure components, like service meshes, or simply by sniffing network connections and traffic. These graphs can be extremely useful for quickly grasping the architecture of the system. They are often annotated with additional monitoring signals, such as the throughput of the individual edges (requests per second), latency percentiles, error counts, and other golden signals indicating the health or performance of a service. Various visualization techniques can be used to enhance the presentation, such as representing relative throughput of the edges with line thickness or even animation (for example, Netflix Vizceral [4]), or color-coding healthy and less healthy nodes. When the application...