Event-driven architecture (EDA) is a popular design pattern for building scalable, high-performance applications. In an event-driven system, events are generated by users or by system components as they occur. These events are then propagated to components that have registered interest in them, so that they can take appropriate action.
Kafka is a popular open-source streaming platform that can be used to build event-driven architectures. Kafka is highly scalable and fault-tolerant, and offers high performance and low latency.
In this article, we'll take a look at how to use Spring Boot and Kafka to build an event-driven architecture. We'll also see how to use Spring Cloud Stream to simplify the development of event-driven microservices.
Before we can start developing our event-driven architecture, we need to set up a Kafka broker. Kafka is available for download from the Confluent website.
Once you've downloaded and extracted Kafka, you can start the broker by running the following command:
bin/kafka-server-start.sh config/server.properties
We'll use Spring Boot to simplify the development of our microservices. Spring Boot makes it easy to create stand-alone, production-grade Spring-based applications.
We can use the Spring Initializr to create a new Spring Boot project. We'll need to select the following dependencies:
Once we've generated the project, we can import it into our IDE of choice.
Our event-driven architecture will consist of a producer that generates events, and a consumer that processes those events. We'll start by developing the producer.
The producer will be a simple Spring Boot application that exposes a REST endpoint. When this endpoint is called, it will generate an event and send it to a Kafka topic.
First, we'll need to create a new Kafka topic. We can do this using the Kafka CLI:
bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --topic events --partitions 1 --replication-factor 1
Next, we'll create a Spring Cloud Stream binding that will send events to our Kafka topic. This binding will be defined in the application.yml
file:
spring:
cloud:
stream:
bindings:
output:
destination: events
content-type: application/json
Now we can create our Spring Boot controller. This controller will expose a /events
endpoint that can be used to generate events:
@RestController
public class EventController {
@Autowired
private MessageChannel output;
@PostMapping("/events")
public void publishEvent(@RequestBody Event event) {
output.send(MessageBuilder.withPayload(event).build());
}
}
The controller is annotated with @RestController
to indicate that it exposes REST endpoints. It also injects a MessageChannel
bean that is used to send messages to the Kafka topic.
Finally, we need to define our Event
class. This class will be used to represent the events that are generated by the producer:
public class Event {
private String id;
private String data;
// Getters and setters
}
Now that we've developed the producer, we can move on to developing the consumer.
The consumer will be a Spring Cloud Stream application that uses Kafka Streams to process the events that are sent to the Kafka topic.
First, we'll create a Spring Cloud Stream binding that will receive events from the Kafka topic. This binding will be defined in the application.yml
file:
spring:
cloud:
stream:
bindings:
input:
destination: events
content-type: application/json
Next, we'll create a Kafka Streams topology that will process the events. This topology will be defined in the EventStreamsConfig
class:
@Configuration
public class EventStreamsConfig {
@Bean
public Topology buildTopology(StreamsBuilder builder) {
// ...
}
}
The buildTopology()
method accepts a StreamsBuilder
as a parameter. We can use this builder to construct our topology.
In our topology, we'll create a stream of events that are read from the Kafka topic. We'll then process this stream using a Kafka Streams processor. This processor will extract the data from the events and print it to the console:
@Configuration
public class EventStreamsConfig {
@Bean
public Topology buildTopology(StreamsBuilder builder) {
Stream<Event> stream = builder.stream("events", Consumed.with(Serdes.String(), new JsonSerde<>(Event.class)));
stream.process(new ProcessorSupplier<String, Event>() {
@Override
public Processor<String, Event> get() {
return new Processor<String, Event>() {
private ProcessorContext context;
@Override
public void init(ProcessorContext context) {
this.context = context;
}
@Override
public void process(String key, Event event) {
String data = event.getData();
System.out.println(data);
}
@Override
public void close() {
}
};
}
});
return builder.build();
}
}
In this topology, we're using the JsonSerde
to serialize and deserialize the events. We could alternatively use the StringSerde
if we wanted to use plain text events.
Now that we've developed the consumer, we can start it up and test it by sending some events to the Kafka topic. We can use the Kafka CLI to produce events:
bin/kafka-console-producer.sh --broker-list localhost:9092 --topic events
And then, in the producer, we can enter some JSON event data:
{"id":"1","data":"Hello, world!"}
If we check the consumer's logs, we should see the event data that we entered:
Hello, world!
In this article, we've seen how to use Spring Boot and Kafka to build an event-driven architecture. We've also seen how to use Spring Cloud Stream to simplify the development of event-driven microservices.