How do you trace requests in Spring applications using Sleuth?

Table of Contents

Introduction

In a microservices architecture, where requests pass through multiple services, it becomes essential to trace and monitor the flow of requests across the system. Spring Cloud Sleuth provides a robust solution for distributed tracing, automatically injecting trace IDs and span IDs into logs to help track requests. This enables better observability and simplifies debugging. By integrating Spring Cloud Sleuth into your Spring-based applications, you can trace requests across multiple services, identify bottlenecks, and troubleshoot performance issues efficiently. This guide explains how to trace requests in Spring applications using Sleuth.

How Spring Cloud Sleuth Traces Requests

1. Automatic Trace ID Propagation

Spring Cloud Sleuth automatically generates a unique trace ID for every incoming request. This trace ID is propagated through all microservices involved in processing the request, allowing you to trace the entire lifecycle of a request.

Sleuth also generates span IDs, which represent individual operations within the trace. A trace can consist of multiple spans, and each span represents a unit of work, such as calling a downstream service or handling a specific part of a request.

Example of Trace and Span:

When a user makes a request to an API Gateway, the trace ID is generated. As the request passes through the authentication service, payment service, and order service, the trace ID remains the same, and each service adds its own span ID.

2. Log Enrichment with Trace Information

Once integrated, Spring Cloud Sleuth automatically enriches your logs with trace and span information. Every log entry related to a specific request will include the trace ID and span ID, making it easy to correlate logs and trace the journey of the request.

Example:

If a request starts in the order-service, a log might look like this:

Here:

  • 1234567890 is the trace ID.
  • order-service is the name of the service where the log was generated.

As the request travels through other services, the trace ID remains consistent, allowing you to group logs from different services and analyze them together.

3. Visualizing Traces with Zipkin or Jaeger

Spring Cloud Sleuth can integrate with distributed tracing systems like Zipkin and Jaeger. These tools collect trace data and allow you to visualize the request flow across microservices. This is particularly useful for analyzing how long each service took to process a request and identifying any performance bottlenecks.

Example with Zipkin:

Once you have Spring Cloud Sleuth integrated with Zipkin, each trace can be visualized in the Zipkin web UI. You can see how the request moved through each service and examine the time taken by each operation. For example, if the payment-service is slow, you can easily spot it in the trace visualization.

Steps to Trace Requests in Spring Applications Using Sleuth

1. Add Spring Cloud Sleuth Dependency

To enable tracing in a Spring Boot application, the first step is to add Spring Cloud Sleuth to your project. You can do this by adding the spring-cloud-starter-sleuth dependency to your pom.xml (Maven) or build.gradle (Gradle).

Maven:

Gradle:

This dependency automatically configures Sleuth to generate and propagate trace and span IDs for requests.

2. Configure Zipkin or Jaeger for Distributed Tracing

To view your traces, you can integrate Sleuth with a tracing backend like Zipkin or Jaeger. Here’s how to configure Zipkin with Spring Cloud Sleuth:

  1. Add Zipkin Dependency:
  1. Configure Zipkin URL:

In your application.properties or application.yml, configure the URL for the Zipkin server (ensure Zipkin is running and accessible).

In the example above, spring.sleuth.sampler.probability=1.0 ensures that all requests are traced. You can adjust this value to sample only a percentage of requests (e.g., 0.1 for 10% of requests).

3. Verify Trace Information in Logs

Once the setup is complete, every request processed by your Spring Boot application will automatically include trace and span IDs. You can view this information in your application logs.

Example Log Entry:

The trace ID 1234567890 will be included in all subsequent log entries related to this request, allowing you to trace it across multiple services.

4. Visualize Traces in Zipkin

Once your application is sending trace data to Zipkin, you can access the Zipkin UI by navigating to http://localhost:9411 in your browser. Here you can:

  • Search for traces by trace ID or service name.
  • View detailed information about the trace, including which services were involved and how long each took to process.
  • Identify any performance issues or failures in the request flow.

Example: Tracing Requests in a Simple Spring Boot Application

Let’s walk through an example where we trace requests in a simple Spring Boot application using Spring Cloud Sleuth and Zipkin.

Step 1: Add Dependencies

In your pom.xml:

Step 2: Configure Application Properties

In application.properties, configure Zipkin and tracing settings:

Step 3: Add a REST Controller

Here’s a simple REST controller that generates logs for each request:

Step 4: Run Zipkin and Your Application

  1. Start Zipkin: You can run Zipkin using Docker:

  2. Run Your Spring Boot Application: Start your Spring Boot application with the logging and tracing configuration.

Step 5: Check Logs and Traces

After making a request to http://localhost:8080/order, you should see the trace ID in the logs, and you can also explore the trace in the Zipkin UI.

Conclusion

Spring Cloud Sleuth makes it easy to trace requests in Spring applications by automatically generating trace IDs and span IDs and propagating them across microservices. With Spring Cloud Sleuth, you gain valuable visibility into the request flow, making it easier to identify bottlenecks, troubleshoot issues, and monitor performance. Integrating Sleuth with distributed tracing systems like Zipkin or Jaeger further enhances the observability of your microservices, providing detailed insights into how requests are handled across the entire system.

By following the steps outlined above, you can easily implement request tracing in your Spring applications and improve your ability to monitor, troubleshoot, and optimize your microservices-based architecture.

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