Getting Started with Apache Kafka and Spring Boot: A Beginner’s Guide

• The world is currently experiencing a data revolution, with massive amounts of real-time data being generated every second. However, many people are unaware of how this data is processed and managed. Enter Apache Kafka — a powerful tool for building event-driven systems.

What is Kafka?

• Apache Kafka is a distributed messaging system that is specifically designed to handle large volumes of real-time data. At its core, Kafka is a publish-subscribe messaging system, which means that producers can publish messages to one or more topics, and subscribers can consume messages from these topics.
• One of the key advantages of Kafka is its ability to guarantee speed, scalability, and durability. Kafka’s unique design enables it to process and manage large amounts of data with ease, making it an ideal choice for building scalable, distributed systems that can handle real-time data processing.
• Kafka achieves its high level of performance through several key design principles. For example, it uses a distributed architecture that allows it to scale horizontally across multiple machines, ensuring that it can handle high levels of throughput. Additionally, Kafka is designed to be fault-tolerant, which means that it can continue to operate even if individual nodes in the cluster fail.

Before developing our spring boot application, we will just go through the basic terminologies in Apache Kafka.

Producer

• A producer is an application or process that sends messages to Kafka topics. The messages themselves can be any type of data, but in Kafka, they are represented as an array of bytes.
• Producers are responsible for sending messages to Kafka, and they do so by publishing messages to one or more topics. The messages are then stored in Kafka in a highly scalable and fault-tolerant manner.

Consumer

• A Kafka consumer is an application or process that receives messages sent by a producer. However, consumers do not receive messages directly from producers. Instead, messages are published to Kafka topics, and consumers subscribe to those topics to receive messages.
• When a consumer subscribes to a topic, it is assigned to one or more partitions within that topic. Each partition is assigned to a specific consumer within the consumer group, ensuring that messages are distributed evenly across all consumers.
• Consumers are responsible for processing the messages that they receive from Kafka. They can be used to perform a wide range of tasks, including real-time processing, analytics, and more.

Kafka Broker

• A Kafka broker is a single instance of the Kafka server that is responsible for handling the storage and processing of messages. Producers and consumers use the broker as an intermediary to send and receive messages.
• Each Kafka broker has its own unique identifier, which is used to distinguish it from other brokers in the cluster. Brokers work together in a cluster to provide a highly scalable and fault-tolerant messaging system.
• When a producer sends a message, it is published to a specific topic on the Kafka broker. The broker then stores the message in a partition within that topic. Consumers can then subscribe to that topic and receive messages from the broker.

Topic

• In Kafka, a topic is a named stream of data that represents a specific category or feed of messages. Producers publish messages to a specific topic, and consumers can subscribe to one or more topics to receive messages.
• Topics provide a way to organize and categorize messages in Kafka. This is important because, as you mentioned, it can be difficult for consumers to know which messages they should consume without some sort of organization.

Okay enough theory lets look the steps of connect the Kafka with Spring Boot

Step 1: Set up a Kafka Broker

• Before we can start using Kafka in our Spring Boot application, we need to have a Kafka broker set up and running. You can download Kafka from the official Apache Kafka website and follow the installation instructions provided.

Step 2: Add Kafka dependencies to your Spring Boot project

• Next, we need to add the necessary Kafka dependencies to our Spring Boot project. You can add the following dependencies to your project’s pom.xml file:

<dependency>
  <groupId>org.springframework.kafka</groupId>
  <artifactId>spring-kafka</artifactId>
  <version>2.7.3</version>
</dependency>

<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>kafka-clients</artifactId>
  <version>2.8.1</version>
</dependency>

Step 3: Configure Kafka in your Spring Boot application

• To configure Kafka in your Spring Boot application, you can use the following properties in your application.properties file

spring.kafka.bootstrap-servers=localhost:9092
spring.kafka.consumer.group-id=my-group
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer

• These properties specify the Kafka bootstrap servers, the consumer group ID, and the serializers and deserializers for the key and value of messages.

Step 4: Create a Kafka Producer

• To create a Kafka producer in your Spring Boot application, you can use the following code:

import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Component;

@Component
public class MyKafkaProducer {

    private final KafkaTemplate<String, String> kafkaTemplate;

    public MyKafkaProducer(KafkaTemplate<String, String> kafkaTemplate) {
        this.kafkaTemplate = kafkaTemplate;
    }

    public void sendMessage(String message) {
        kafkaTemplate.send("my-topic", message);
    }
}

• This code creates a Kafka producer that sends messages to a topic named “my-topic”. You can customize this code to fit your specific use case.

Step 5: Create a Kafka Consumer

• To create a Kafka consumer in your Spring Boot application, you can use the following code:

import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

@Component
public class MyKafkaConsumer {

    @KafkaListener(topics = "my-topic", groupId = "my-group")
    public void listen(String message) {
        System.out.println("Received message: " + message);
    }
}

• This code creates a Kafka consumer that listens for messages on a topic named “my-topic” and prints out the message when it is received.
• That’s it! With these steps, you should now have a basic Spring Boot application that can produce and consume messages using Apache Kafka.

Conclusion

• Apache Kafka is a powerful tool for building real-time data processing systems that can handle large volumes of data. By leveraging its unique design and architecture, developers can build scalable, distributed systems that can process and manage data with ease.
• In this blog, we have explored the basics of Kafka and learned how to develop a Spring Boot application that uses Kafka for messaging. We covered the key concepts of producers, consumers, brokers, and topics, and demonstrated how to create a Kafka producer and consumer in Spring Boot.
• I hope that this blog has been helpful in getting you started with Apache Kafka and Spring Boot, and that it has provided a solid foundation for further exploration and experimentation.