This is replaced by https://github.com/openzipkin/brave-example
This is an example app where two Spring Boot (Java) services collaborate on an http request. Notably, timing of these requests are recorded into Zipkin, a distributed tracing system. This allows you to see the how long the whole operation took, as well how much time was spent in each service.
Here's an example of what it looks like
This example was initially made for a Distributed Tracing Webinar on June 30th, 2016. There's probably room to enroll if it hasn't completed, yet, and you are interested in the general topic.
Web requests are served by Spring MVC controllers, and tracing is automatically performed for you by Spring Cloud Sleuth.
This example intentionally avoids advanced topics like async and load balancing, even though Spring Cloud Sleuth supports that, too. Once you get familiar with things, you can play with more interesting Spring Cloud components.
This example has two services: frontend and backend. They both report trace data to Zipkin. To setup the demo, you need to start Frontend, Backend and Zipkin.
Once the services are started, open http://localhost:8081/
- This will call the backend (http://localhost:9000/api) and show the result, which defaults to a formatted date.
Next, you can view traces that went through the backend via http://localhost:9411/?serviceName=backend
- This is a locally run Zipkin service which keeps traces in memory
In a separate tab or window, start each of sleuth.webmvc.Frontend and sleuth.webmvc.Backend:
$ ./mvnw compile exec:java -Dexec.mainClass=sleuth.webmvc.Backend
$ ./mvnw compile exec:java -Dexec.mainClass=sleuth.webmvc.Frontend
Next, run Zipkin, which stores and queries traces reported by the above services.
curl -sSL https://zipkin.io/quickstart.sh | bash -s
java -jar zipkin.jar
- The service name in the Zipkin UI defaults to the application name
spring.application.name=frontend
- All incoming requests are sampled and that decision is honored downstream.
spring.sleuth.sampler.probability=1.0
- The below pattern adds trace and span identifiers into log output
logging.pattern.level=%d{ABSOLUTE} [%X{traceId}/%X{spanId}] %-5p [%t] %C{2} - %m%n
- If you pass the header
user_name
Brave will automatically propagate it to the backend!curl -s localhost:8081 -H'user_name: JC'
A distributed trace will only include connections that are configured (instrumented). You may be using some libraries that aren't automatically configured.
Here are a few small examples that showcase how to stitch-in commonly requested features.
git checkout add-webflux-tracing
This changes the
example to serve requests with reactive Mono
controllers, using WebClient
instead of
RestTemplate
to make the call from the frontend to the backend.
git checkout add-apachehc-tracing
This changes the
example to use Apache HttpClient
instead of RestTemplate
to make the
call from the frontend to the backend.
https://github.com/openzipkin/brave/tree/master/instrumentation/httpclient
git checkout add-mysql-tracing
This changes the example to read the timestamp from MySQL instead of the Spring Boot Process. It adds a brave tracing interceptor to add details to the existing trace.
https://github.com/openzipkin/brave/tree/master/instrumentation/mysql8
git checkout add-rabbit-tracing
This changes the example to invoke the backend with RabbitMQ instead of WebMVC. Sleuth automatically configures Brave's spring-rabbit to add trace details.
https://github.com/openzipkin/brave/tree/master/instrumentation/spring-rabbit
git checkout add-kafka-tracing
This changes the example to invoke the backend with Kafka instead of WebMVC. Sleuth automatically configures Brave's kafka-clients instrumentation when spring-kafka is present.
https://github.com/openzipkin/brave/tree/master/instrumentation/kafka-clients https://github.com/spring-cloud/spring-cloud-sleuth/blob/v2.1.1.RELEASE/spring-cloud-sleuth-core/src/main/java/org/springframework/cloud/sleuth/instrument/messaging/TraceMessagingAutoConfiguration.java#L110
This changes the example to invoke the backend with ActiveMQ instead of WebMVC. Sleuth automatically configures Spring JmsTemplate and JmsListener to add trace details.
git checkout add-dubbo-tracing
This changes the example to call a Dubbo backend instead of WebMVC. It uses Brave's RPC filter to add details to the existing trace.
https://github.com/openzipkin/brave/tree/master/instrumentation/dubbo-rpc
git checkout add-jfr-context
This changes the example to add trace IDs to Java Flight recorder "Zipkin/Scope" events.
https://github.com/openzipkin/brave/tree/master/context/jfr
git checkout add-opentracing
This changes the example to add a lookup tag using the default
SpanCustomizer
and OpenTracing's Tracer api. Users can choose which
api makes most sense for them to expose to business code.
Under the covers, this uses the brave-opentracing bridge:
https://github.com/openzipkin-contrib/brave-opentracing
A docker image containing the example can be built using
$ docker build -t openzipkin/example-sleuth-webmvc -f docker/Dockerfile .
The backend can be started with a command similar to
$ docker run -it --rm -p 9000:9000 openzipkin/example-sleuth-webmvc backend
The frontend can be started with a command similar to
$ docker run -it --rm -p 8081:8081 openzipkin/example-sleuth-webmvc frontend
Sleuth layers on the Brave project, so can re-use any code that works with brave. It can also use transports besides http to send data to a Zipkin compatible service.
Contact us on gitter if you need more help!