In the world of distributed systems, the likelihood of components failing or becoming unresponsive is higher compared to monolithic systems. Given the interdependence of microservices or modules in a distributed setup, the failure of one component can lead to cascading failures throughout the system, potentially causing the entire system to malfunction or shut down. Therefore, resilience — the ability of a system to handle and recover from failures — becomes critically important in distributed environments.
Much like how an electrical circuit breaker prevents an overload by stopping the flow of electricity when excessive current is detected, the Circuit Breaker pattern in software engineering stops the flow of requests to a service when the number of failures exceeds a predefined threshold. This ensures that a failing service doesn’t continue receiving traffic until it recovers, preventing further strain and potential cascading failures.
The Circuit Breaker pattern is designed to detect failures and encapsulates the logic of preventing a system from executing an operation that’s set to fail. Instead of repeatedly making requests to a service that is likely unavailable or facing issues, the circuit breaker stops all attempts for a while, giving the troubled service time to recover.