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Distributed Tracing With OpenTelemetry and Jaeger In Spring Boot 3

Distributed Tracing With OpenTelemetry and Jaeger In Spring Boot 3
6 min read

In my previous article “Distributed Tracing With Spring Cloud Jaeger”, we had seen how we can collect distributed traces from a Spring Boot application using Opentracing.

If you are not familiar with distributed tracing, you can read this article wherein I have explained what are traces and spans in distributed systems.

The Opentracing project has been archived, as a result of it being merged with OpenCensus to form a single universal framework for application tracing and metrics.

This new framework is called OpenTelemetry.

OpenTelemetry (OTel) is an open-source framework for collecting and analyzing observability data, like traces and metrics, from distributed systems. It provides APIs and libraries for developers to instrument their applications, gain insights into system performance, and integrate with various observability tools.

Let’s look at how we can send distributed traces to Jaeger using Opentelemetry.

Creating an application

Let’s go to and create an application with the following dependencies.

  • Spring Web (required to create REST endpoints)
  • Spring Boot Actuator

We will be using the micrometer collector in the actuator dependency to collect the traces and then use the OpenTelemetry dependency to export the traces.

For this, we would need to add the following dependencies.


The dependency versions will be taken care of by the Spring Boot parent.

Next, we will create two endpoints in our application in the Controller class.

 private RestTemplate restTemplate;

    private String applicationName;

    public Controller(RestTemplate restTemplate) {
        this.restTemplate = restTemplate;

    public ResponseEntity path1() {"Incoming request at {} for request /path1 ", applicationName);
        String response = restTemplate.getForObject("http://localhost:8090/service/path2", String.class);
        return ResponseEntity.ok("response from /path1 + " + response);

    public ResponseEntity path2() {"Incoming request at {} at /path2", applicationName);
        return ResponseEntity.ok("response from /path2 ");

The idea here is to run the same application two times with different ports, such that one application calls the other applications on a different path.

When we invoke the /path1 endpoint, it will further call the /path2 endpoint on the predefined port 8090 of the server running on localhost.

Now to export the spans to Jaeger, we need to create a span exporter bean as follows.

OtlpHttpSpanExporter otlpHttpSpanExporter(@Value("${tracing.url}") String url) {
    return OtlpHttpSpanExporter.builder()

Along with this, we will define the Jaeger URL in the properties file to which the traces are to be reported.

    name: app

  url: http://localhost:4318/v1/traces

      probability: 1.0

    level: '%5p [${},%X{traceId:-},%X{spanId:-}]'

Now here we are setting the probability of sampling the tracing to 1 so that every trace and span is reported to Jaeger.

We will also provide a custom logging format, so we can see the spans and traces in the application logs.

Now, before we start the application, let’s start Jaeger using docker-compose.

Starting Jaeger with Docker

To start Jaeger, we have the following docker-compose file.

version: '3.9'
    image: jaegertracing/all-in-one:latest
      - 4318:4318
      - 16686:16686

For Jaeger to support the OpenTelemetry input format, we need to set the COLLECTOR_OTLP_ENABLED to true

With this, let's start the application as two separate instances on different ports.

java -jar \
target/Distributed-Service-0.0.1-SNAPSHOT.jar \ \
java -jar \
target/Distributed-Service-0.0.1-SNAPSHOT.jar \ \

Once the two applications are up and running, we call the endpoint /path1 on the first server.

curl localhost:8080/service/path1

Now, let’s visualize the traces in Jaeger UI.

To access the Jaeger UI, open the following URL.


When we select the service and click find traces, we will see the traces in the UI.

Jaeger UI

Let’s open the trace and see the various spans of the request.

Traces and spans

Here we can see the various span and how much time each span took along with span id. You can correlate the spans with the log lines of each of the services as shown below.

Service-1 log:

INFO [Service-1,9b888edfe46d05bfe3bd06f690bff0af,012c9c0ff054e356] 17505 --- [nio-8080-exec-2] com.amrut.prabhu.Controller: Incoming request at Service-1 for request /path1
Service-2 log:
INFO [Service-2,9b888edfe46d05bfe3bd06f690bff0af,cf99518ce5d57ac9] 22322 --- [nio-8090-exec-1] com.amrut.prabhu.Controller: Incoming request at Service-2 at /path2

You can find the complete code on my GitHub repository here.

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