Tracing in Spring Boot Microservices Using Zipkin

In this post, we will learn Tracing in Spring Boot Microservices Using Zipkin.

Tracing in Spring Boot Microservices Using Zipkin

Introduction

In today's complex microservices architectures, understanding the flow of requests across various services is crucial for effective monitoring and debugging. Tracing is a powerful technique that allows us to track requests as they propagate through different microservices. In this blog post, we will explore how to implement tracing in Spring Boot microservices using Zipkin. We'll provide a step-by-step guide along with a working example to help you get started.

Table of Contents

1. What is Tracing and Why is it Important?

2. Introducing Zipkin

3. Setting Up Zipkin Server

4. Instrumenting Spring Boot Microservices

5. Propagating Tracing Information

6. Analyzing Traces in Zipkin UI

7. Conclusion

1. What is Tracing and Why is it Important?

Tracing involves capturing and monitoring the flow of requests across multiple services in a distributed system. It helps in understanding how requests traverse different microservices, which aids in identifying bottlenecks, performance issues, and detecting errors.

By implementing tracing in your microservices architecture, you can gain insights into request latency, visualize the entire request flow, and efficiently diagnose and resolve issues.

2. Introducing Zipkin

Zipkin is an open-source distributed tracing system that helps track and visualize requests as they flow through a microservices architecture. It provides powerful tools for debugging and analyzing the behavior of distributed systems. Zipkin offers a user-friendly web-based UI to visualize traces and identify latency and error patterns.

3. Setting Up Zipkin Server

To begin, we need to set up a Zipkin server that will collect and store trace information from our microservices. Follow these steps:

Step 1: Add Zipkin Server Dependency

In your Spring Boot project, add the following Maven or Gradle dependency to enable the Zipkin server:

<dependency>

    <groupId>org.springframework.cloud</groupId>

    <artifactId>spring-cloud-starter-zipkin</artifactId>

</dependency>

Step 2: Configure Zipkin Server

Create a configuration class to enable the Zipkin server and specify the server's URL. Add the following code:

import org.springframework.context.annotation.Configuration;

import zipkin2.server.internal.EnableZipkinServer;

@Configuration

@EnableZipkinServer

public class ZipkinServerConfig {

}

Step 3: Start Zipkin Server

Run your Spring Boot application. Zipkin server will start on the default port `9411`. Access the server at `http://localhost:9411` to verify if it's running successfully.

4. Instrumenting Spring Boot Microservices

Now that the Zipkin server is up and running, let's instrument our Spring Boot microservices to send tracing information.

Step 1: Add Zipkin Client Dependency

In each microservice's `pom.xml` file, add the following Maven or Gradle dependency to enable the Zipkin client:

<dependency>

    <groupId>org.springframework.cloud</groupId>

    <artifactId>spring-cloud-starter-zipkin</artifactId>

</dependency>

Step 2: Configure Microservice for Zipkin

In each microservice's configuration file (`application.properties` or `application.yml`), add the following properties:

spring.zipkin.base-url=http://localhost:9411

spring.zipkin.service.name=my-service-name

Replace `my-service-name` with the actual name of the microservice.

Step 3: Enable Tracing

In each microservice, open the main class or a configuration class and add the `@EnableZipkinTracing` annotation:

import org.springframework.cloud.sleuth.zipkin2.Enable

ZipkinTracing;

@EnableZipkinTracing

@SpringBootApplication

public class MyMicroserviceApplication {

    // ...

}

5. Propagating Tracing Information

To ensure tracing information is propagated across microservices, we need to add headers to outgoing requests. The `Brave` library provides instrumentation for different HTTP clients.

Step 1: Add Brave Dependencies

In each microservice's `pom.xml` file, add the appropriate Brave dependency based on the HTTP client you are using. For example, if you're using Apache HttpClient:

<dependency>

    <groupId>org.springframework.cloud</groupId>

    <artifactId>spring-cloud-starter-zipkin</artifactId>

</dependency>

<dependency>

    <groupId>io.zipkin.brave</groupId>

    <artifactId>brave-instrumentation-apache-httpclient</artifactId>

</dependency>

Step 2: Configure HTTP Client

In the microservice where you're using the HTTP client, configure it to propagate tracing information. Here's an example using Apache HttpClient:

import brave.http.HttpTracing;

import brave.spring.web.TracingClientHttpRequestInterceptor;

import org.apache.http.impl.client.HttpClients;

import org.springframework.context.annotation.Bean;

import org.springframework.http.client.ClientHttpRequestInterceptor;

import org.springframework.http.client.HttpComponentsClientHttpRequestFactory;

import org.springframework.web.client.RestTemplate;

@Configuration

public class HttpClientConfig {

    

    @Bean

    public RestTemplate restTemplate(HttpTracing httpTracing) {

        CloseableHttpClient httpClient = HttpClients.custom()

                .addInterceptorLast(new TracingClientHttpRequestInterceptor(httpTracing))

                .build();

        RestTemplate restTemplate = new RestTemplate(new HttpComponentsClientHttpRequestFactory(httpClient));

        restTemplate.setInterceptors(Collections.singletonList((ClientHttpRequestInterceptor) new TracingClientHttpRequestInterceptor(httpTracing)));

        return restTemplate;

    }

}

6. Analyzing Traces in Zipkin UI

With tracing implemented and information propagated, let's explore the Zipkin UI to analyze traces.

Step 1: Generate Traces

Make some requests to your microservices either manually or programmatically. Ensure that requests span across multiple microservices to see the complete trace.

Step 2: View Traces in Zipkin UI

Open the Zipkin server's URL (`http://localhost:9411`) in your browser. You should see a list of recorded traces. Click on a trace to view detailed information such as span durations, service dependencies, and more.

7. Conclusion

Tracing plays a vital role in understanding and diagnosing issues in distributed systems. By implementing tracing in Spring Boot microservices using Zipkin, you can gain insights into the request flow, identify performance bottlenecks, and effectively debug your microservices architecture.

In this blog post, we covered the importance of tracing, introduced Zipkin as a tracing system, and provided a step-by-step guide on how to set up Zipkin server, instrument Spring Boot microservices, propagate tracing information, and analyze traces in the Zipkin UI.

With the knowledge gained from this guide, you are well-equipped to implement tracing in your Spring Boot microservices and leverage Zipkin to gain valuable insights into your distributed system.

Happy tracing!