🛡️ Resilience Patterns in Distributed Systems

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll explore patterns that help distributed systems remain resilient under failure conditions.

Why Resilience Patterns Matter

In distributed systems, failures are inevitable. Resilience patterns help:

• Prevent cascading failures
• Maintain availability
• Improve user experience during partial outages

1. Circuit Breaker

Stops requests to a failing service to prevent overwhelming it:

// Using Resilience4j circuit breaker
CircuitBreaker circuitBreaker = CircuitBreaker.ofDefaults("service");
Supplier decorated = CircuitBreaker
    .decorateSupplier(circuitBreaker, () -> remoteService.call());
String result = Try.ofSupplier(decorated)
    .recover(throwable -> "fallback").get();

2. Bulkhead

Isolates resources to prevent one failing part from affecting others:

// Using Resilience4j bulkhead
Bulkhead bulkhead = Bulkhead.ofDefaults("serviceBulkhead");
Supplier decorated = Bulkhead
    .decorateSupplier(bulkhead, () -> remoteService.call());
String result = Try.ofSupplier(decorated)
    .recover(throwable -> "fallback").get();

3. Failover & Retry

Automatically retry failed requests or switch to a backup service:

// Simple retry logic
Retry retry = Retry.ofDefaults("serviceRetry");
Supplier decorated = Retry.decorateSupplier(retry, () -> remoteService.call());
String result = Try.ofSupplier(decorated)
    .recover(throwable -> "fallback").get();

Next in the Series

In the next post, we’ll explore Service Discovery & Load Balancing, including registry-based and client-side strategies.

Label for this post: Distributed Systems