Span Data as Messages

You can accumulate and send span data over Spring Cloud Stream by including the spring-cloud-sleuth-stream jar as a dependency, and adding a Channel Binder implementation (e.g. spring-cloud-starter-stream-rabbit for RabbitMQ or spring-cloud-starter-stream-kafka for Kafka). This will automatically turn your app into a producer of messages with payload type Spans.

Zipkin Consumer

There is a special convenience annotation for setting up a message consumer for the Span data and pushing it into a Zipkin SpanStore. This application

@SpringBootApplication
@EnableZipkinStreamServer
public class Consumer {
    public static void main(String[] args) {
        SpringApplication.run(Consumer.class, args);
    }
}

will listen for the Span data on whatever transport you provide via a Spring Cloud Stream Binder (e.g. include spring-cloud-starter-stream-rabbit for RabbitMQ, and similar starters exist for Redis and Kafka). If you add the following UI dependency

<groupId>io.zipkin.java</groupId>
<artifactId>zipkin-autoconfigure-ui</artifactId>

Then you’ll have your app a Zipkin server, which hosts the UI and api on port 9411.

The default SpanStore is in-memory (good for demos and getting started quickly). For a more robust solution you can add MySQL and spring-boot-starter-jdbc to your classpath and enable the JDBC SpanStore via configuration, e.g.:

spring:
  rabbitmq:
    host: ${RABBIT_HOST:localhost}
  datasource:
    schema: classpath:/mysql.sql
    url: jdbc:mysql://${MYSQL_HOST:localhost}/test
    username: root
    password: root
# Switch this on to create the schema on startup:
    initialize: true
    continueOnError: true
  sleuth:
    enabled: false
zipkin:
  storage:
    type: mysql

Custom Consumer

A custom consumer can also easily be implemented using spring-cloud-sleuth-stream and binding to the SleuthSink. Example:

@EnableBinding(SleuthSink.class)
@SpringBootApplication(exclude = SleuthStreamAutoConfiguration.class)
@MessageEndpoint
public class Consumer {

    @ServiceActivator(inputChannel = SleuthSink.INPUT)
    public void sink(Spans input) throws Exception {
        // ... process spans
    }
}

In order to customize the polling mechanism you can create a bean of PollerMetadata type with name equal to StreamSpanReporter.POLLER. Here you can find an example of such a configuration.

@Configuration
public static class CustomPollerConfiguration {

    @Bean(name = StreamSpanReporter.POLLER)
    PollerMetadata customPoller() {
        PollerMetadata poller = new PollerMetadata();
        poller.setMaxMessagesPerPoll(500);
        poller.setTrigger(new PeriodicTrigger(5000L));
        return poller;
    }
}