Tracing a reactive flow – Using Spring Cloud Sleuth with Boot 2

Biju KunjummenJune 22nd, 2018Last Updated: June 22nd, 2018

0 486 1 minute read

Spring Cloud Sleuth which adds Spring instrumentation support on top of OpenZipkin Brave makes distributed tracing trivially simple for Spring Boot applications. This is a quick write up on what it takes to add support for distributed tracing using this excellent library.

Consider two applications – a client application which uses an upstream service application, both using Spring WebFlux, the reactive web stack for Spring:

My objective is to ensure that flows from user to the client application to the service application can be traced and latencies cleanly recorded for requests.

The final topology that Spring Cloud Sleuth enables is the following:

The sampled trace information from the client and the service app is exported to Zipkin via a queuing mechanism like RabbitMQ.

So what are the changes required to the client and the service app – like I said it is trivially simple! The following libraries need to be pulled in – in my case via gradle:

compile("org.springframework.cloud:spring-cloud-starter-sleuth")
 compile("org.springframework.cloud:spring-cloud-starter-zipkin")
 compile("org.springframework.amqp:spring-rabbit")

The versions are not specified as they are expected to be pulled in via Spring Cloud BOM and thanks to Spring Gradle Dependency Management plugin:

ext {
    springCloudVersion = 'Finchley.RELEASE'
}

apply plugin: 'io.spring.dependency-management'

dependencyManagement {
    imports {
        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${springCloudVersion}"
    }
}

And that is actually it, any logs from the application should now start recording the trace and the spans, see how he traceid carried forward in the following logs spanning two different services:

2018-06-22 04:06:28.579  INFO [sample-client-app,c3d507df405b8aaf,c3d507df405b8aaf,true] 9 --- [server-epoll-13] sample.load.PassThroughHandler           : handling message: Message(id=null, payload=Test, delay=1000)
2018-06-22 04:06:28.586  INFO [sample-service-app,c3d507df405b8aaf,829fde759da15e63,true] 8 --- [server-epoll-11] sample.load.MessageHandler               : Handling message: Message(id=5e7ba240-f97d-405a-9633-5540bbfe0df1, payload=Test, delay=1000)

Further the Zipkin UI records the exported information and can visually show a sample trace the following way:

This sample is available in my github repository here – https://github.com/bijukunjummen/sleuth-webflux-sample and can be started up easily using docker-compose with all the dependencies wired in.

Published on Java Code Geeks with permission by Biju Kunjummen, partner at our JCG program. See the original article here: Tracing a reactive flow – Using Spring Cloud Sleuth with Boot 2

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