Top 10 Spring Kafka Interview Questions

In this post, we are going to discuss top 10 spring Kafka interview questions that are asked by most companies.

These questions are asked to many candidates, so if you are preparing for an interview then you should go through all the questions and answers mentioned here.

1.What is the role of KafkaHeaders in Spring Kafka?

Kakfa headers provide a constant for kafka messages, whenever we consume any message in a class or method that is annotated to @kafkalistner, we may require the metadata information then we can use Kafka headers, it contains many parameters like topic name, partition,offset, key, value etc.

2. Explain Kafka Transaction in Spring Kafka?

Let’s first understand how Kafka application work, so as we know that kafka application work in ‘consume-process-produce‘ pattern

3. How do you configure concurrent message consumption in Spring Kafka consumers?

We can configure the concurrency level using the ‘concurrency‘ property in @kafkalistner annotation

@KafkaListener(topics = “myTopic”, concurrency = “3”) public void listen(String message) { System.out.println(“Received Message: ” + message); }

4. How do you handle serialization and deserialization in Spring Kafka?

You can configure serializers and deserializes using properties like ‘key.serializer‘,’value.serializer‘, key.deserializer’ and value.deserializer in the kafka producer and consumer configuration

Let’s take an example of how you can configure in your producer and consumer configuration

Producer side configuration:

key-serializer     :      org.apache.kafka.common.serialization.StringSerializer
value-serializer :      org.apache.kafka.common.serialization.StringSerializer

Consumer side configuration:

 key-deserializer:  org.apache.kafka.common.serialization.StringDeserialize
 value-deserializer: org.apache.kafka.common.serialization..StringDesrializer

5. How can you monitor Spring Kafka applications?

Using Micrometer we can monitor the Spring Kafka application

from starting with version 2.3 , the listener container will automatically create and update the micrometer timer for the listener if a micrometer is detected on the classpath and a single metaRegistry is present in the application context.

Two timers are maintained – one for successful calls to the listener and one for failures.

The timers are named spring.kafka.listener and have the following tags:

• name : (container bean name)
• result : success or failure
• exception : none or ListenerExecutionFailedException

we can add additional tags using the ContainerProperties‘s micrometerTags property

6. How Can we Test Spring Kafka?

To test Spring Kafka applications: below are the 4 important point we have to consider

1. Unit Testing:
   • Mock dependencies like KafkaTemplate.
   • Test business logic independently.
   • Verify producer behavior.
2. Integration Testing:
   • Use embedded Kafka or Docker containers.
   • Test Kafka configuration.
   • Verify consumer and producer behavior.
3. Spring Testing Support:
   • Utilize @SpringBootTest and @EmbeddedKafka.
   • Consider @DirtiesContext for context cleanup.
4. End-to-End Testing:
   • Simulate the entire message flow.
   • Validate application behavior as a whole.

7. What are the advantages of using Spring Kafka over the native Kafka client?

Spring Kafka Offers several advantages over using the native kafka client

1. Simplified Configuration: Spring Kafka provides a simplified and more declarative approach to configuring Kafka components using Spring’s dependency injection and configuration management.
2. Integration with Spring Ecosystem: Spring Kafka seamlessly integrates with other Spring projects and frameworks, such as Spring Boot, Spring Cloud, and Spring Integration, allowing for easier development and management of Kafka-based applications within the broader Spring ecosystem.
3. Abstraction and Encapsulation: Spring Kafka abstracts away many of the complexities of interacting with Kafka, providing higher-level abstractions and encapsulating boilerplate code, which can result in cleaner and more maintainable code.
4. Simplified Error Handling: Spring Kafka simplifies error handling by providing built-in mechanisms for handling exceptions, retries, and dead-letter queues, reducing the amount of custom error-handling code that developers need to write.
5. Easy Testing: Spring Kafka’s support for testing through mock objects, embedded Kafka instances, and Spring’s testing infrastructure makes it easier to write comprehensive unit and integration tests for Kafka-based applications.
6. Transaction Support: Spring Kafka provides support for transactional messaging, allowing developers to easily implement end-to-end transactional workflows across multiple Kafka topics or partitions.
7. Monitoring and Management: Spring Kafka integrates with Spring Boot Actuator, providing out-of-the-box support for monitoring and managing Kafka-based applications, including metrics, health checks, and management endpoints.

8.Explain KafkaListenerEndpointRegistry in Spring Kafka.

KafkaListenerEndpointRegistry in Spring Kafka is a central manager for Kafka message listener endpoints.

It handles below things:

1. Endpoint Registration,

2. Lifecycle management,

3. Concurrency control,

4. Dynamic management,

and Error handling within a Spring application. It simplifies the management of Kafka message consumers and integrates seamlessly with Spring’s lifecycle.

Example Usage: Imagine you have two Kafka listeners defined with @KafkaListener annotations, but you only want to start one listener initially. You can inject the KafkaListenerEndpointRegistry and use it to start the desired listener programmatically:

9. How do you configure error handling in Spring Kafka consumers?

There are mainly 4 ways to handle errors in spring Kafka,but still we can handle error in our use case so lets start.

1. Error Handling with @KafkaListener:

• we can specify an error handler method within the @KafkaListener annotation using the errorHandler attribute.

@KafkaListener(topics = "myTopic", errorHandler = "myErrorHandler")
public void listen(String message) {
    // Message processing logic
}

@Bean
public ErrorHandler myErrorHandler() {
    return new MyErrorHandler();
}

2. Custom Error Handler Implementation:

• Implement the ErrorHandler interface to create a custom error handler.
• Override the handle(Exception ex, ConsumerRecord<?, ?> data) method to define how errors should be handled.

public class MyErrorHandler implements ErrorHandler {
    @Override
    public void handle(Exception ex, ConsumerRecord<?, ?> data) {
        // Error handling logic
    }
}

3. Error Handling with SeekToCurrentErrorHandler:

• Spring Kafka provides a built-in error handler implementation called SeekToCurrentErrorHandler.
• This error handler seeks the consumer back to the current offset on error, allowing for retries.
• You can configure it as the default error handler for all @KafkaListener annotations in your application. For example:

@Bean
public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
    ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
    factory.setConsumerFactory(consumerFactory());
    factory.setErrorHandler(new SeekToCurrentErrorHandler());
    return factory;
}

4. Dead-Letter Topic:

• Configure a dead-letter topic where failed messages are sent for further analysis or processing.
• You can use the DeadLetterPublishingRecoverer provided by Spring Kafka to automatically publish failed messages to a dead-letter topic.

@Bean
public DeadLetterPublishingRecoverer deadLetterPublishingRecoverer(KafkaTemplate<Object, Object> kafkaTemplate) {
    return new DeadLetterPublishingRecoverer(kafkaTemplate);
}

10. How do you produce messages to Kafka using Spring Kafka?

To produce messages to Kafka using Spring Kafka, you typically follow these steps:

1. Configure Kafka Producer Properties: Define the necessary Kafka producer properties, such as bootstrap servers, key and value serializers, and any other relevant configurations. This can be done either in the application properties file or programmatically.
2. Create a KafkaTemplate Bean: Define a KafkaTemplate bean in your Spring configuration. KafkaTemplate provides a high-level abstraction for interacting with Kafka producers.
3. Produce Messages: Inject the KafkaTemplate bean into your service or component where you want to produce messages. Use the send() method of KafkaTemplate to produce messages to Kafka topics. You need to specify the topic name, key (optional), and value for each message.

Here’s a code example demonstrating these steps:

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;

@Service
public class KafkaProducerService {

    private final KafkaTemplate<String, String> kafkaTemplate;

    @Autowired
    public KafkaProducerService(KafkaTemplate<String, String> kafkaTemplate) {
        this.kafkaTemplate = kafkaTemplate;
    }

    public void sendMessage(String topic, String key, String message) {
        kafkaTemplate.send(topic, key, message);
    }
}

In the above example:

• We define a KafkaProducerService class that injects a KafkaTemplate<String, String> bean via constructor injection.
• The sendMessage() method sends a message to a specified Kafka topic with an optional key.

I hope these questions and answers will help when you are preparing for kafka interview, we have listed here top 10 spring kafka interview questions, please comment if you have any suggestion or doubt.