⚡ Fault Tolerance & Reliability in Distributed Systems

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll explore how to design systems that remain reliable even when parts of the system fail.

Why Fault Tolerance Matters

Distributed systems are prone to failures: network issues, server crashes, or service downtime. Fault tolerance ensures the system continues operating correctly despite these failures.

Common Fault Tolerance Patterns

• 🔁 Retries — automatically retry failed operations.
• 💡 Idempotency — ensure repeated operations don’t produce duplicate effects.
• 📦 Replication — duplicate data across nodes to handle failures.
• 🚪 Circuit Breakers — prevent cascading failures by stopping calls to failing services.
• 📊 Bulkheads — isolate parts of the system to limit failure impact.

Retry Example in Java

int retries = 3;
boolean success = false;

while(!success && retries > 0) {
    try {
        externalService.call();
        success = true;
    } catch (Exception e) {
        retries--;
        if(retries == 0) {
            throw e;
        }
        Thread.sleep(1000); // wait before retry
    }
}

Idempotent Operation Example

// Using a unique requestId to ensure idempotency
if (!processedRequests.contains(requestId)) {
    processRequest(request);
    processedRequests.add(requestId);
}

Next in the Series

In the next post, we’ll explore Communication Patterns in distributed systems, including REST, gRPC, and message brokers like Kafka.

Label for this post: Distributed Systems