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# Implementing Circuit Breakers with Resilience4j/Polly
- URL: https://stalin-pereira.com/implementing-circuit-breakers-with-resilience4j-polly/
- Published: 2025-12-26T09:09:00.000Z
- Updated: 2026-10-16T19:08:16.000Z
- Description: Implementing patterns to stop cascading failures in services
- Author: Stalin Pereira
- Tags: Distributed Systems

**Don't Let One Service Kill the Platform**

How to implement Circuit Breakers to stop cascading failure.

## The 'Christmas Tree' Light Effect

- **Old Lights** — One bulb goes out, the entire string goes dark.
- **Microservices** — The 'Recommendation Service' is slow. Now the 'Homepage' is waiting... and crashing.
- **Resource Exhaustion** — Your healthy services run out of threads waiting for the sick service.

## The Circuit Breaker Pattern

Closed, Open, Half-Open.

- **Closed (Normal)** — Traffic flows freely. Failures are counted.
- **Open (Broken)** — Error threshold reached (e.g., 50% fail). Traffic is blocked instantly.
- **Fast Fail** — The caller gets an immediate error instead of waiting 30s for a timeout.

## The Recovery: Half-Open

- **Testing the Waters** — After a cooldown (e.g., 60s), allow 1 request through.
- **Success** — If it works, close the circuit. Resume normal traffic.
- **Failure** — If it fails, open the circuit again. Wait longer.

## Tools: Resilience4j & Polly

- **Java (Resilience4j)** — Annotation based. `@CircuitBreaker(name = "backendA")`.
- **.NET (Polly)** — Fluent API. `Policy.Handle<Exception>().CircuitBreaker(...)`.

## Fallback Logic

- **Graceful Degradation** — If Recommendations are down, show 'Most Popular Items' from a cache.
- **User Experience** — The user sees a slightly worse page, not a 500 error page.

## Summary: Fail Fast

Protect your resources.

> It is better to refuse a request instantly than to hang efficiently.

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Do your failures cascade or isolate?