📡 Communication Patterns in Distributed Systems

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll explore how distributed nodes communicate reliably and efficiently.

Why Communication Patterns Matter

Distributed systems rely on network communication. Choosing the right pattern affects performance, reliability, and scalability.

1. REST (Representational State Transfer)

REST is a popular synchronous HTTP-based communication pattern:

• Simple, widely supported
• Stateless requests
• Easy to debug and monitor

// Spring Boot REST client example
@RestController
public class OrderController {
    @GetMapping("/orders/{id}")
    public Order getOrder(@PathVariable Long id) {
        return orderService.findOrder(id);
    }
}

2. gRPC

gRPC is a high-performance RPC framework using Protocol Buffers:

• Supports streaming
• Strongly typed contracts
• Lower latency than REST

// gRPC service definition example
service OrderService {
    rpc GetOrder(OrderRequest) returns (OrderResponse);
}

3. Asynchronous Messaging (Kafka)

Kafka allows asynchronous, decoupled communication between services:

• Producers send events to topics
• Consumers read events independently
• Supports high throughput and fault tolerance

// Kafka producer example
producer.send(new ProducerRecord<>("orders", orderId, order));

Next in the Series

In the next post, we’ll explore Resilience Patterns such as circuit breakers, bulkheads, and failover strategies in distributed systems.

Label for this post: Distributed Systems