Understanding Distributed Tracing with Spring Cloud Sleuth and Zipkin

Introduction: The article explains the principles and practice of distributed tracing in microservice architectures, focusing on integrating Spring Cloud Sleuth and Zipkin into the open‑source PassJava project.

It describes why tracing is needed when services are split and logic is complex, and introduces core concepts such as Span, Trace, Annotation, and how a Trace ID links spans together.

Implementation steps include adding Spring Cloud dependencies and Sleuth starter via Maven, configuring logging, and running the relevant microservices (gateway, question, admin). Example Maven snippets:

<dependencyManagement>
    <dependencies>
        <!-- Spring Cloud dependencies -->
        <dependency>
            <groupId>org.springframework.cloud</groupId>
            <artifactId>spring-cloud-dependencies</artifactId>
            <version>Hoxton.SR3</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
    </dependencies>
</dependencyManagement>

<dependency>
    <groupId>org.springframework.cloud</groupId>
    <artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>

Configuration properties for Sleuth and Zipkin are also provided:

# zipkin server address
spring.zipkin.base-url=http://192.168.56.10:9411/
spring.zipkin.discovery-client-enabled=false
spring.zipkin.sender.type=web
spring.sleuth.sampler.probability=1

The article then covers Zipkin’s architecture (Collection, Storage, API, UI) and the tracing flow, followed by Docker commands to start Zipkin and optionally use Elasticsearch for storage:

docker run -d -p 9411:9411 openzipkin/zipkin

docker run --env STORAGE_TYPE=elasticsearch --env ES_HOSTS=192.168.56.10:9200 openzipkin/zipkin-dependencies

Testing steps show how to invoke APIs, view logs, and interpret Zipkin UI results, including performance metrics such as request transmission time, server processing time, and total latency.

Conclusion: The article summarizes the core tracing concepts, demonstrates Sleuth + Zipkin integration in a real project, and provides links to the open‑source repository for further exploration.