Exploring Spring Cloud Stream Kafka Binder Consumer Interceptor

Introduction

Spring Cloud Stream is a framework that simplifies the development of message-driven microservices by abstracting message brokers such as Apache Kafka and RabbitMQ. One of the powerful features of Spring Cloud Stream is its ability to integrate seamlessly with Kafka, allowing developers to build robust and scalable event-driven applications. The Kafka binder in Spring Cloud Stream provides a way to connect to Kafka topics easily.

In this blog, we'll delve into how to use a consumer interceptor with Spring Cloud Stream Kafka Binder. Interceptors in Kafka provide a mechanism to intercept and alter records before they are consumed by the application, offering opportunities for logging, metrics collection, and data manipulation.

Prerequisites

Before diving into the details, make sure you have the following prerequisites:

• Java Development Kit (JDK) 8 or later
• Apache Kafka
• Spring Boot 2.x or later
• Maven or Gradle

Setting Up the Spring Boot Application

First, let's set up a simple Spring Boot project with the necessary dependencies for Spring Cloud Stream and Kafka.

Maven pom.xml

<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.cloud</groupId>
        <artifactId>spring-cloud-starter-stream-kafka</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-test</artifactId>
        <scope>test</scope>
    </dependency>
</dependencies>

<dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>org.springframework.cloud</groupId>
            <artifactId>spring-cloud-dependencies</artifactId>
            <version>Hoxton.SR10</version>
            <type>pom</type>
            <scope>import</scope>
        </dependency>
    </dependencies>
</dependencyManagement>

Gradle build.gradle

dependencies {
    implementation 'org.springframework.boot:spring-boot-starter'
    implementation 'org.springframework.cloud:spring-cloud-starter-stream-kafka'
    testImplementation 'org.springframework.boot:spring-boot-starter-test'
}

dependencyManagement {
    imports {
        mavenBom "org.springframework.cloud:spring-cloud-dependencies:Hoxton.SR10"
    }
}

Configuring Kafka Binder

Next, configure the Kafka binder in the application.yml file.

spring:
  cloud:
    stream:
      bindings:
        input:
          destination: my-topic
          group: my-group
          consumer:
            interceptor-classes: com.example.MyConsumerInterceptor
      kafka:
        binder:
          brokers: localhost:9092

Creating a Kafka Consumer Interceptor

To create a consumer interceptor, implement the ConsumerInterceptor interface provided by Kafka. This interface allows you to define custom logic for intercepting and processing records before they reach the application.

package com.example;

import org.apache.kafka.clients.consumer.ConsumerInterceptor;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.common.Configurable;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.Map;

public class MyConsumerInterceptor implements ConsumerInterceptor<String, String>, Configurable {

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

    @Override
    public ConsumerRecords<String, String> onConsume(ConsumerRecords<String, String> records) {
        records.forEach(record -> {
            logger.info("Intercepted record: key = {}, value = {}", record.key(), record.value());
            // Add your custom logic here
        });
        return records;
    }

    @Override
    public void onCommit(Map offsets) {
        // Custom logic on commit
    }

    @Override
    public void close() {
        // Cleanup resources if necessary
    }

    @Override
    public void configure(Map<String, ?> configs) {
        // Configuration logic
    }
}

Creating the Consumer Application

Create a simple consumer application that listens to messages from a Kafka topic.

package com.example;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.cloud.stream.annotation.EnableBinding;
import org.springframework.cloud.stream.annotation.StreamListener;
import org.springframework.messaging.Message;

@SpringBootApplication
@EnableBinding(KafkaProcessor.class)
public class KafkaConsumerApplication {

    public static void main(String[] args) {
        SpringApplication.run(KafkaConsumerApplication.class, args);
    }

    @StreamListener("input")
    public void handle(Message<String> message) {
        System.out.println("Received message: " + message.getPayload());
    }
}

Interface for Binding

Define an interface for binding the input channel to the Kafka topic.

package com.example;

import org.springframework.cloud.stream.annotation.Input;
import org.springframework.messaging.SubscribableChannel;

public interface KafkaProcessor {
    String INPUT = "input";

    @Input(INPUT)
    SubscribableChannel input();
}

Running the Application

1. Start the Kafka broker and create the required topic (my-topic).
2. Run the Spring Boot application.

When messages are produced to the Kafka topic, the MyConsumerInterceptor will intercept the records, and you should see the intercepted log messages.

Conclusion

In this blog, we've explored how to use a consumer interceptor with Spring Cloud Stream Kafka Binder. Interceptors provide a powerful way to process, log, and manipulate records before they are consumed by the application. By integrating custom interceptors, you can enhance the functionality of your Kafka consumers, adding valuable capabilities such as logging, metrics collection, and data transformation.

By following the steps outlined in this guide, you should be able to implement and configure consumer interceptors in your Spring Cloud Stream applications seamlessly. Happy coding!