Spring Boot and Sleuth: Distributed Tracing for Microservices

In the world of microservices, managing and monitoring numerous services can become quite a complex task. Distributed tracing provides a way to track and visualize the flow of requests across multiple services, allowing for better observability and debugging. One of the powerful tools for implementing distributed tracing in Spring Boot applications is Spring Cloud Sleuth.

What is Distributed Tracing?

Distributed tracing is a method used to follow and record the path of requests as they travel through different components or services in a distributed system. It helps in identifying performance bottlenecks, errors, and understanding the latency issues by providing a clear map of where and how data flows.

Why Use Spring Cloud Sleuth?

Spring Cloud Sleuth adds trace and span IDs to logs, making it easier to correlate log entries across services. It integrates seamlessly with popular logging frameworks such as Logback and SLF4J. Sleuth also integrates well with tools like Zipkin, which collects and visualizes the tracing data.

Setting Up Spring Boot with Sleuth

Step 1: Add Dependencies

First, you need to add the necessary dependencies to your pom.xml or build.gradle file. For Maven, it looks like this:


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

Step 2: Configuration

By default, Spring Cloud Sleuth is auto-configured. You can customize it by adding properties in your application.properties or application.yml:


spring.zipkin.base-url=http://localhost:9411
spring.sleuth.sampler.probability=1.0

The spring.zipkin.base-url points to the Zipkin server, and spring.sleuth.sampler.probability controls the sampling rate (1.0 means every request will be traced).

How Sleuth Works

Sleuth intercepts requests at various points in your application and attaches trace and span IDs to each request. These IDs propagate through the entire request lifecycle, enabling you to track the request across service boundaries.

Example with REST Controller

Here’s a simple REST controller to demonstrate how Sleuth works:


@RestController
public class SleuthController {

    private final Logger logger = LoggerFactory.getLogger(SleuthController.class);

    @GetMapping("/trace")
    public String trace() {
        logger.info("Handling /trace request");
        return "Tracing request with Sleuth!";
    }
}

In the logs, you’ll see entries with trace and span IDs, allowing you to correlate logs across different services.

Visualization with Zipkin

To visualize the traces, you need to set up Zipkin. You can start Zipkin as a Docker container:


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

Access the Zipkin UI at http://localhost:9411 to see the traces. Here you can filter and analyze the trace data to understand the latency and identify bottlenecks.

Conclusion

Spring Cloud Sleuth, combined with Zipkin, provides a powerful solution for distributed tracing in microservices. It enhances observability, making it easier to debug and monitor applications. By adding trace and span IDs to logs, it gives you the ability to follow the flow of requests and understand the performance characteristics of your services.

Integrate Sleuth into your Spring Boot applications today and take your monitoring and debugging to the next level!

Spring Boot and Sleuth