🎯 Event-Driven Architecture in Distributed Systems

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll explore Event-Driven Architecture (EDA) and how it enables scalable, decoupled distributed systems.

Why Event-Driven Architecture?

EDA decouples services through events, allowing asynchronous communication and improving scalability, responsiveness, and fault tolerance.

1. Key Concepts

• Event: A record of something that happened in the system.
• Event Producer: Service that publishes events.
• Event Consumer: Service that reacts to events.
• Event Broker: Middleware (like Kafka) that routes events from producers to consumers.

2. Kafka Example

Kafka is a popular distributed event streaming platform. Here’s a simple Java producer and consumer example:

// Producer
Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer producer = new KafkaProducer<>(props);

producer.send(new ProducerRecord<>("orders-topic", orderId, orderJson));
producer.close();

// Consumer
Properties consumerProps = new Properties();
consumerProps.put("bootstrap.servers", "localhost:9092");
consumerProps.put("group.id", "order-service");
consumerProps.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
consumerProps.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

KafkaConsumer consumer = new KafkaConsumer<>(consumerProps);
consumer.subscribe(Arrays.asList("orders-topic"));

while (true) {
    ConsumerRecords records = consumer.poll(Duration.ofMillis(100));
    for (ConsumerRecord record : records) {
        System.out.println("Processing order: " + record.value());
    }
}

3. Event Sourcing

Instead of storing only current state, store a sequence of events that describe state changes:

• Replay events to reconstruct state
• Works well with CQRS (Command Query Responsibility Segregation)

// Example: storing an order created event
OrderCreatedEvent event = new OrderCreatedEvent(orderId, orderDetails);
eventStore.append(event);

4. Benefits

• Decoupled, scalable architecture
• Asynchronous processing reduces latency for users
• Improved fault tolerance

Next in the Series

In the next post, we’ll explore Monitoring and Alerting in Event-Driven Systems to ensure your asynchronous workflows stay healthy.

Label for this post: Distributed Systems