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In the above example, we are creating one more ConcurrentKafkaListenerContainerFactory for JSON serialization. It allows us to convert any Java object to bytes. In this example, the producer application writes Kafka data to a topic in your Kafka cluster. Step 1: Set Up the Spring Kafka Dependencies Before you proceed further to set up Spring Kafka Consumer and Producer, let’s configure the required Kafka and Spring Boot dependencies. Apache Kafka is an open-source distributed event streaming platform used by thousands of. The spring-kafka JSON serializer and deserializer use the Jackson library, which is also an optional Maven dependency for the spring-kafka project. Spring Kafka provides JsonSerializer and JsonDeserializer implementations that are based on the Jackson JSON object mapper. Be sure to use the promo code SPRING101 for 101 of free Confluent Cloud usage. Import .Avro and Confluent Cloud Schema Registry ¶ To get started with your own Spring Boot and Confluent Cloud project using Spring Initialzr, the Confluent Cloud Console, as well as Java code, you can follow the exercise on Confluent Developer. You need to include this dependency into your project: Maven. Demonstrates setup of batch processing and batch error handling. Source Code - Configure Kafka Topic in OrderService Microservice import. Spring Integration for Apache Kafka is based on the Spring for Apache Kafka project. You will have to create two different ProducerFactory below is example import .producer.ProducerConfig Next start the Spring Boot Application by running it as a Java Application. a Spring Boot application with Kafka consumer endpoints, internal storage and web interfaces. spring-kafka-registrytargetgeneratedavro mvn generate-sources The generated source code comes in very handy to process messages in our application.