What does the circuit breaker pattern do in a microservices architecture?

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Multiple Choice

What does the circuit breaker pattern do in a microservices architecture?

Explanation:
The circuit breaker pattern protects a microservices system by stopping calls to a failing dependency once failures exceed a threshold, so the rest of the system can continue operating and recover instead of getting bogged down by a cascading failure. When a dependency is healthy, calls pass through normally (closed state). If too many failures occur within a monitoring window, the circuit opens, and subsequent requests fail fast or are redirected to a fallback, allowing the failing service time to recover without being overwhelmed. After a timeout, the pattern lets a limited set of test calls through (half-open) to see if the dependency has recovered, and it will close again if those attempts succeed; otherwise, it reopens. Disabling caching isn’t what the circuit breaker does. It isn’t about scaling dependencies automatically, nor about compressing requests or forcing fresh data. Its purpose is fault isolation and rapid resilience in the face of downstream failures.

The circuit breaker pattern protects a microservices system by stopping calls to a failing dependency once failures exceed a threshold, so the rest of the system can continue operating and recover instead of getting bogged down by a cascading failure. When a dependency is healthy, calls pass through normally (closed state). If too many failures occur within a monitoring window, the circuit opens, and subsequent requests fail fast or are redirected to a fallback, allowing the failing service time to recover without being overwhelmed. After a timeout, the pattern lets a limited set of test calls through (half-open) to see if the dependency has recovered, and it will close again if those attempts succeed; otherwise, it reopens.

Disabling caching isn’t what the circuit breaker does. It isn’t about scaling dependencies automatically, nor about compressing requests or forcing fresh data. Its purpose is fault isolation and rapid resilience in the face of downstream failures.

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