How do you create a custom Kafka producer configuration in Spring Boot?

Table of Contents

• Introduction
• Steps to Create a Custom Kafka Producer Configuration in Spring Boot
  • 1. Add Kafka Dependencies
    • Maven (pom.xml):
    • Gradle (build.gradle):
  • 2. Configure Kafka Producer Settings in **application.yml** or **application.properties**
    • Example application.yml:
  • 3. Create a Custom Kafka Producer Configuration Class
    • Example: Custom Kafka Producer Configuration
  • 4. Using the Custom Kafka Producer in a Service
    • Example: Kafka Producer Service
  • 5. Verify the Custom Kafka Producer
    • Example: Controller to Test Producer
  • 6. Run the Application
• Conclusion

Introduction

In a Spring Boot application, Kafka producers are responsible for sending messages to Kafka topics. A custom Kafka producer configuration allows you to fine-tune producer settings, such as the message serialization method, Kafka broker details, and producer-specific properties.

This guide will walk you through the steps to create a custom Kafka producer configuration in Spring Boot, including how to configure serialization, set custom producer properties, and enable different message delivery settings.

Steps to Create a Custom Kafka Producer Configuration in Spring Boot

1. Add Kafka Dependencies

To use Kafka in your Spring Boot application, you need to include the spring-kafka dependency in your project.

Maven (pom.xml):

Gradle (build.gradle):

2. Configure Kafka Producer Settings in **application.yml** or **application.properties**

In Spring Boot, the simplest way to configure Kafka properties is through the application.yml or application.properties file. You can specify Kafka broker details, producer-specific settings, and message serializers.

Example application.yml:

• **bootstrap-servers**: The address of the Kafka brokers.
• **key-serializer**: The serializer used for the key part of the message.
• **value-serializer**: The serializer used for the value part of the message.
• **acks**: Defines the level of acknowledgment required from the broker (e.g., all, 1, or 0).
• **retries**: The number of retry attempts in case of failure.
• **batch-size**: The maximum size of a batch of messages to send.

3. Create a Custom Kafka Producer Configuration Class

While configuring Kafka properties in the application.yml or application.properties file is sufficient for most cases, you might want to create a custom configuration class to control the Kafka producer settings programmatically.

Example: Custom Kafka Producer Configuration

• **producerFactory()**: Defines the producer factory that creates Kafka producers.
• **producerConfigs()**: Contains the producer configuration settings.
• **kafkaTemplate()**: A Spring Kafka KafkaTemplate bean to send messages.

4. Using the Custom Kafka Producer in a Service

Now that we have a custom Kafka producer configuration, we can use it to send messages to Kafka topics. Spring Boot provides the KafkaTemplate class, which is an abstraction that simplifies sending messages to Kafka topics.

Example: Kafka Producer Service

• **sendMessage** method: Sends messages to the test-topic Kafka topic using the KafkaTemplate.

5. Verify the Custom Kafka Producer

To test the custom Kafka producer, you can call the sendMessage method from a REST controller or directly from the application.

Example: Controller to Test Producer

• **/send** endpoint: This REST endpoint allows you to send a message to the Kafka topic by providing the message as a query parameter.

6. Run the Application

Once everything is set up, you can run your Spring Boot application. When you call the /send endpoint with a message, the producer will send it to the specified Kafka topic, and you will see it in the Kafka logs.

Conclusion

Creating a custom Kafka producer configuration in Spring Boot involves setting up Kafka properties such as broker addresses, serializers, and producer settings like retries and acknowledgments. With Spring Kafka, you can easily configure and customize the Kafka producer to meet the needs of your application. Whether you are sending simple messages or complex objects, customizing the Kafka producer configuration ensures that your application interacts with Kafka efficiently and according to your business requirements.