Apache Kafka Support

Apache Kafka is supported by providing auto-configuration of the spring-kafka project.

Kafka configuration is controlled by external configuration properties in spring.kafka.*. For example, you might declare the following section in application.properties:

Properties
YAML

spring.kafka.bootstrap-servers=localhost:9092
spring.kafka.consumer.group-id=myGroup

spring:
  kafka:
    bootstrap-servers: "localhost:9092"
    consumer:
      group-id: "myGroup"

To create a topic on startup, add a bean of type NewTopic. If the topic already exists, the bean is ignored.

See KafkaProperties for more supported options.

Sending a Message

Spring’s KafkaTemplate is auto-configured, and you can autowire it directly in your own beans, as shown in the following example:

Java
Kotlin

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

@Component
public class MyBean {

	private final KafkaTemplate<String, String> kafkaTemplate;

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

	// ...

	public void someMethod() {
		this.kafkaTemplate.send("someTopic", "Hello");
	}

}

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

@Component
class MyBean(private val kafkaTemplate: KafkaTemplate<String, String>) {

	// ...

	fun someMethod() {
		kafkaTemplate.send("someTopic", "Hello")
	}

}

If the property spring.kafka.producer.transaction-id-prefix is defined, a KafkaTransactionManager is automatically configured. Also, if a RecordMessageConverter bean is defined, it is automatically associated to the auto-configured KafkaTemplate.

Receiving a Message

When the Apache Kafka infrastructure is present, any bean can be annotated with @KafkaListener to create a listener endpoint. If no KafkaListenerContainerFactory has been defined, a default one is automatically configured with keys defined in spring.kafka.listener.*.

The following component creates a listener endpoint on the someTopic topic:

Java
Kotlin

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

@Component
public class MyBean {

	@KafkaListener(topics = "someTopic")
	public void processMessage(String content) {
		// ...
	}

}

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

@Component
class MyBean {

	@KafkaListener(topics = ["someTopic"])
	fun processMessage(content: String?) {
		// ...
	}

}

If a KafkaTransactionManager bean is defined, it is automatically associated to the container factory. Similarly, if a RecordFilterStrategy, CommonErrorHandler, AfterRollbackProcessor or ConsumerAwareRebalanceListener bean is defined, it is automatically associated to the default factory.

Depending on the listener type, a RecordMessageConverter or BatchMessageConverter bean is associated to the default factory. If only a RecordMessageConverter bean is present for a batch listener, it is wrapped in a BatchMessageConverter.

A custom ChainedKafkaTransactionManager must be marked @Primary as it usually references the auto-configured KafkaTransactionManager bean.

Kafka Streams

Spring for Apache Kafka provides a factory bean to create a StreamsBuilder object and manage the lifecycle of its streams. Spring Boot auto-configures the required KafkaStreamsConfiguration bean as long as kafka-streams is on the classpath and Kafka Streams is enabled by the @EnableKafkaStreams annotation.

Enabling Kafka Streams means that the application id and bootstrap servers must be set. The former can be configured using spring.kafka.streams.application-id, defaulting to spring.application.name if not set. The latter can be set globally or specifically overridden only for streams.

Several additional properties are available using dedicated properties; other arbitrary Kafka properties can be set using the spring.kafka.streams.properties namespace. See also Additional Kafka Properties for more information.

To use the factory bean, wire StreamsBuilder into your @Bean as shown in the following example:

Java
Kotlin

import java.util.Locale;

import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KeyValue;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.Produced;

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafkaStreams;
import org.springframework.kafka.support.serializer.JsonSerde;

@Configuration(proxyBeanMethods = false)
@EnableKafkaStreams
public class MyKafkaStreamsConfiguration {

	@Bean
	public KStream<Integer, String> kStream(StreamsBuilder streamsBuilder) {
		KStream<Integer, String> stream = streamsBuilder.stream("ks1In");
		stream.map(this::uppercaseValue).to("ks1Out", Produced.with(Serdes.Integer(), new JsonSerde<>()));
		return stream;
	}

	private KeyValue<Integer, String> uppercaseValue(Integer key, String value) {
		return new KeyValue<>(key, value.toUpperCase(Locale.getDefault()));
	}

}

import org.apache.kafka.common.serialization.Serdes
import org.apache.kafka.streams.KeyValue
import org.apache.kafka.streams.StreamsBuilder
import org.apache.kafka.streams.kstream.KStream
import org.apache.kafka.streams.kstream.Produced
import org.springframework.context.annotation.Bean
import org.springframework.context.annotation.Configuration
import org.springframework.kafka.annotation.EnableKafkaStreams
import org.springframework.kafka.support.serializer.JsonSerde

@Configuration(proxyBeanMethods = false)
@EnableKafkaStreams
class MyKafkaStreamsConfiguration {

	@Bean
	fun kStream(streamsBuilder: StreamsBuilder): KStream<Int, String> {
		val stream = streamsBuilder.stream<Int, String>("ks1In")
		stream.map(this::uppercaseValue).to("ks1Out", Produced.with(Serdes.Integer(), JsonSerde()))
		return stream
	}

	private fun uppercaseValue(key: Int, value: String): KeyValue<Int?, String?> {
		return KeyValue(key, value.uppercase())
	}

}

By default, the streams managed by the StreamBuilder object are started automatically. You can customize this behavior using the spring.kafka.streams.auto-startup property.

Additional Kafka Properties

The properties supported by auto configuration are shown in the Integration Properties section of the Appendix. Note that, for the most part, these properties (hyphenated or camelCase) map directly to the Apache Kafka dotted properties. See the Apache Kafka documentation for details.

Properties that don’t include a client type (producer, consumer, admin, or streams) in their name are considered to be common and apply to all clients. Most of these common properties can be overridden for one or more of the client types, if needed.

Apache Kafka designates properties with an importance of HIGH, MEDIUM, or LOW. Spring Boot auto-configuration supports all HIGH importance properties, some selected MEDIUM and LOW properties, and any properties that do not have a default value.

Only a subset of the properties supported by Kafka are available directly through the KafkaProperties class. If you wish to configure the individual client types with additional properties that are not directly supported, use the following properties:

Properties
YAML

spring.kafka.properties[prop.one]=first
spring.kafka.admin.properties[prop.two]=second
spring.kafka.consumer.properties[prop.three]=third
spring.kafka.producer.properties[prop.four]=fourth
spring.kafka.streams.properties[prop.five]=fifth

spring:
  kafka:
    properties:
      "[prop.one]": "first"
    admin:
      properties:
        "[prop.two]": "second"
    consumer:
      properties:
        "[prop.three]": "third"
    producer:
      properties:
        "[prop.four]": "fourth"
    streams:
      properties:
        "[prop.five]": "fifth"

This sets the common prop.one Kafka property to first (applies to producers, consumers, admins, and streams), the prop.two admin property to second, the prop.three consumer property to third, the prop.four producer property to fourth and the prop.five streams property to fifth.

You can also configure the Spring Kafka JsonDeserializer as follows:

Properties
YAML

spring.kafka.consumer.value-deserializer=org.springframework.kafka.support.serializer.JsonDeserializer
spring.kafka.consumer.properties[spring.json.value.default.type]=com.example.Invoice
spring.kafka.consumer.properties[spring.json.trusted.packages]=com.example.main,com.example.another

spring:
  kafka:
    consumer:
      value-deserializer: "org.springframework.kafka.support.serializer.JsonDeserializer"
      properties:
        "[spring.json.value.default.type]": "com.example.Invoice"
        "[spring.json.trusted.packages]": "com.example.main,com.example.another"

Similarly, you can disable the JsonSerializer default behavior of sending type information in headers:

Properties
YAML

spring.kafka.producer.value-serializer=org.springframework.kafka.support.serializer.JsonSerializer
spring.kafka.producer.properties[spring.json.add.type.headers]=false

spring:
  kafka:
    producer:
      value-serializer: "org.springframework.kafka.support.serializer.JsonSerializer"
      properties:
        "[spring.json.add.type.headers]": false

Properties set in this way override any configuration item that Spring Boot explicitly supports.

Testing with Embedded Kafka

Spring for Apache Kafka provides a convenient way to test projects with an embedded Apache Kafka broker. To use this feature, annotate a test class with @EmbeddedKafka from the spring-kafka-test module. For more information, please see the Spring for Apache Kafka reference manual.

To make Spring Boot auto-configuration work with the aforementioned embedded Apache Kafka broker, you need to remap a system property for embedded broker addresses (populated by the EmbeddedKafkaBroker) into the Spring Boot configuration property for Apache Kafka. There are several ways to do that:

Provide a system property to map embedded broker addresses into spring.kafka.bootstrap-servers in the test class:

Java
Kotlin

	static {
		System.setProperty(EmbeddedKafkaBroker.BROKER_LIST_PROPERTY, "spring.kafka.bootstrap-servers");
	}

	init {
		System.setProperty(EmbeddedKafkaBroker.BROKER_LIST_PROPERTY, "spring.kafka.bootstrap-servers")
	}

Configure a property name on the @EmbeddedKafka annotation:

Java
Kotlin

import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.kafka.test.context.EmbeddedKafka;

@SpringBootTest
@EmbeddedKafka(topics = "someTopic", bootstrapServersProperty = "spring.kafka.bootstrap-servers")
class MyTest {

	// ...

}

import org.springframework.boot.test.context.SpringBootTest
import org.springframework.kafka.test.context.EmbeddedKafka

@SpringBootTest
@EmbeddedKafka(topics = ["someTopic"], bootstrapServersProperty = "spring.kafka.bootstrap-servers")
class MyTest {

	// ...

}

Use a placeholder in configuration properties:

Properties
YAML

spring.kafka.bootstrap-servers=${spring.embedded.kafka.brokers}

spring:
  kafka:
    bootstrap-servers: "${spring.embedded.kafka.brokers}"