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  4. An Introduction to Distributed Tracing and Zipkin [Video]

An Introduction to Distributed Tracing and Zipkin [Video]

You can debug latency problems using call graphs created by Zipkin. This can be tricky as requests can fan out across polyglot components and even data centers.

Pieter Humphrey user avatar by
Pieter Humphrey
CORE ·
Feb. 04, 17 · Presentation
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Latency analysis is the act of blaming components for causing user-perceptible delay. In today’s world of microservices, this can be tricky as requests can fan out across polyglot components and even data centers. In many cases, the root source of latency isn’t a component, but rather a link between components.

This session will overview how to debug latency problems using call graphs created by Zipkin. We’ll use trace Zipkin itself, setting up from scratch using Docker. While we’re at it, we’ll discuss how the model works, and how to safely trace production. Finally, we’ll overview the ecosystem, including tools to trace Ruby, C#, Java, and Spring Boot apps.

When you leave, you’ll at least know something about distributed tracing, and hopefully be on your way to blaming things for causing latency!

You can see the slides here and watch the video below.

Spring Framework Fan-out (software) Spring Boot app Debug (command) Data (computing) Production (computer science) microservice Session (web analytics)

Published at DZone with permission of Pieter Humphrey, DZone MVB. See the original article here.

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