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How to Configure Kafka in Spring Boot

Last Updated on September 18, 2022 by Climent Rick

As Apache Kafka continues to grow in popularity, more and more businesses are looking to incorporate it into their technology stack. Spring Boot is a popular framework for building Java applications, and Kafka is a natural fit for use with SpringBoot applications due to its simple integration. In this article, we’ll show you how to configure Kafka in Spring Boot.

Spring Boot with Spring Kafka Producer Example | Tech Primers

  • Kafka is a distributed streaming platform
  • Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can “just run”
  • In this tutorial, we will be integrating Kafka with Spring Boot
  • We will be using the spring-kafka dependency for integration purposes
  • This dependency brings in all the required Kafka related jars into our project
  • org
  • springframework
  • kafka spring-kafka 5
  • First, we need to configure the Kafka broker details and topic information in application properties file: spring
  • kafka: bootstrap_servers=localhost:9092 # comma delimited list of host:port pairs of brokers to connect to for bootstrapping metadata about topics, partitions etc (Kerberos principal used only if security protocol is SASL_PLAINTEXT or SASL_SSL) sasl_mechanism=GSSAPI # Kerberos mechanism used for connection to brokers(valid values are GSSAPI and PLAIN)
  • The default value is null which means no security protocol configured (valid values are PLAINTEXT and SSL); If not set, SASL authentication is disabled; When configuring client authentication across multiplebrokers with different mechanisms you must use the same mechanism when setting up your brokers as well; Different JAAS configuration files may also be necessary depending on your environment settings(for example when working with ActiveMQ Artemis 2
  • * it’s recommended that you use org/apache/activemq/artemis/spi/core/security/) security_protocol=SASL_PLAINTEXT# Protocol used to communicate with brokers (valid values are PLAINTEXT, SSL and SASL_PLAINTEXT); The default value is PLAINTEXT; If not set , then SSL encryption enabled by default if server certificates available ; When configuring client authentication across multiplebrokers with different protocols you must use the same protocol when setting up your brokers as well;Different JAAS configuration files may also be necessary depending on your environment settings(for example when working with ActiveMQ Artemis 2
  • * it’s recommended that you use org/apache/activemq/artemis

Apache Kafka Spring Boot Microservices Example

Microservices have become a popular architectural style for building cloud-native applications. Apache Kafka is often used as a message bus or event streaming platform for these types of applications. In this post, we’ll take a look at how to use Kafka in a Spring Boot application with both producers and consumers.

We’ll also see how to configure Spring Cloud Stream to use Kafka as its underlying message broker.

Spring Boot Kafka Configuration Properties

If you’re looking to configure Spring Boot for use with Kafka, there are a few different properties that you’ll need to set. In this blog post, we’ll take a look at the most important Spring Boot Kafka configuration properties and how they can be used to fine-tune your application’s behavior. The first property that we’ll look at is spring.kafka.bootstrap-servers .

This property specifies the comma-separated list of host:port pairs that the application will use to connect to the Kafka brokers. By default, this property is set to localhost:9092 , which will only work if you have a single broker running on your local machine. If you have multiple brokers, or if your brokers are not running on the default port ( 9092 ), then you’ll need to update this property accordingly.

For example, if you have two brokers running on host1:9092 and host2:9093 , then you would set spring.kafka.bootstrap-servers=host1:9092,host2:9093 . The next property we’ll look at is spring.kafka.consumer . This property contains a map of consumer configs that will be passed to the KafkaConsumer factory when creating consumers in your application.

The most important configs that can be set here are group_id , enable_auto_commit , auto_commit_interval_ms , and key_deserializer . The group_id config is used to specify what group this particular consumer belongs to. All consumers in the same group will consume messages from the same partitions in a topic (i.e., they will share state).

Therefore, it’s important that each consumer in your application has a unique group id so that they don’t interfere with each other’s processing of messages. The enable_auto_commit config controls whether or not offsets are automatically committed back to Kafka after each message is processed by the consumer (offsets are stored per partition per consumer group). If this config is set to true (the default), then offsets will be automatically committed every 5 seconds (this interval can be changed by setting the auto\_commit\_interval\_ms config).

Kafka Connect Spring Boot Example

Kafka Connect is a tool for streaming data between Apache Kafka and other systems. It is built on top of the Kafka Producer and Consumer APIs. Kafka Connect can be used to stream data from any source system into Kafka, and from Kafka to any sink system.

In this example, we will use Kafka Connect to stream data from a Spring Boot application into Kafka, and from Kafka back out to another Spring Boot application. We will use two Spring Boot applications. The first application will generate random data that we will send to Kafka using the Kafka Producer API.

The second application will consume that data from Kafka using the Kafka Consumer API. The source code for this example is available on GitHub.

Spring Boot Kafka Producer Consumer Example

In this article, we’ll cover Spring Boot Kafka Producer and Consumer Example. We’ll also take a look at how to set up a Spring Boot project to use the Confluent Platform. The example will use a Spring Boot application that uses Apache Kafka as its message broker.

The producer and consumer components in the sample application will be written in Java. We’ll start by creating a new Spring Boot project with the name kafka-producer-consumer-example. You can find the complete source code for this project on GitHub.

Once the project is created, we need to add dependencies for Kafka and Zookeeper in our build file. For this example, we’ll be using version 2.2 of Kafka and version 3.4 of ZooKeeper.

org.springframework.kafka spring-kafka

2..2..1
” >> pom…xml $ git add . && git commit -m “Added dependencies” [master (root-commit) 7a3b7f6] Added dependencies 4 files changed, 177 insertions(+) create mode 100644 .gitignore create mode 100644 pom…xml create mode 100644 src/main//resources//application….properties create …mode …100644 src///main////java////com////example////producerconsumerExampleApplication…kt”$ git push –set–upstream origin master Enumerating objects: 6, done….

Counting objects: 100% (6), done… Delta compression using up to 8 threads Compressing objects: 100% (5/5), done…

Spring Boot Kafka Producer Example

In this example, we’ll be creating a simple Spring Boot application that produces messages and sends them to a Kafka topic. We’ll also configure our producer to use Avro Serialization. We’ll start by creating a Maven project with the following dependencies:

spring-boot-starter-web – for exposing our producer as a REST endpoint spring-kafka – for working with Kafka in Spring Boot applications avro – for using Avro serialization in our producer

Once we have our project set up, we can define our message model using Avro. Our message will have two fields – name and age. The full schema definition is as follows:

{ “namespace”: “com.example”, “type”: “record”, “name”: “Person”, “fields”: [ {“name”: “name”, “type”: “string”}, {“name”: “age”, “type”: “int”} ] } Now that we have our data model defined, we can create our Kafka Producer class. This class will be responsible for sending messages to the Kafka topic.

We’ll inject some configuration values into this class so that it can connect to the Kafka broker and produce messages: @ConfigurationProperties(prefix = “kafka”) public class KafkaProducerConfig { private String bootstrapServers; //Getters and setters omitted } @Autowired private KafkaProducerConfig config; …

How to Configure Kafka in Spring Boot
How to Configure Kafka in Spring Boot 2

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How Set Kafka Property in Spring Boot?

Kafka is a distributed streaming platform. It is used for building real-time data pipelines and streaming apps. It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies.

In this post we will see how to set Kafka property in Spring boot application. We can use application.properties or application.yml file to configure Kafka properties in Spring boot applications. Let’s say we want to set the following Kafka parameters:

broker.id=0 //The id of the broker.

How Do I Use Spring Boot With Kafka?

Spring Boot is a Java-based framework used for developing microservices. It is developed by Pivotal Software. Microservices are services that are small and self-contained.

They can be deployed independently and communicate with each other using APIs. Kafka is a distributed streaming platform that can be used to build real-time data pipelines and streaming applications. It is often used in conjunction with Apache Storm, Apache Hadoop, and Apache Spark.

Spring Boot allows developers to create stand-alone, production-grade Spring based Applications that they can just run. We don’t need to deploy our application to an Application Server anymore. This drastically reduces the time required for starting up new projects or writing tests because there’s no need to worry about configuring an Application Server anymore – it just works out of the box!

How Do You Implement Kafka Listener in Spring Boot?

Kafka is a distributed streaming platform. It is used for building real-time data pipelines and streaming apps. It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies.

In this post we will see how to implement a Kafka listener in Spring boot. We will create a simple message producer and consumer that listens to a topic and prints the messages to the console. The first thing we need is to add the Kafka dependency to our pom.xml:

org.apache.kafka kafka-clients

2.0.0
We also need the spring-kafka dependency:

org.springframework.kafka spring-kafka

1.3.8. We can now create our KafkaConfig class that will hold our Kafka configuration:

What is Kafka in Spring Boot?

Kafka is a distributed stream processing platform that Spring Boot can use for event-driven microservices. It provides an opinionated configuration to set up both producers and consumers. You can use the KafkaTemplate to produce records and the @KafkaListener annotation to consume them.

Conclusion

Kafka is a powerful tool for processing streaming data. In this post, we’ll take a look at how to configure Kafka in Spring Boot. We’ll cover the basics of setting up a Kafka server, creating topics, and sending and receiving messages.

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