Circuit Breaker Pattern
Explore the Circuit Breaker pattern to understand how it acts as a stateful proxy that monitors downstream services and prevents cascading failures in microservices. Learn the pattern's three states, key parameters, implementation basics, and the importance of monitoring and tuning for system reliability.
A single slow database query is all it takes for one downstream dependency to start responding in 30 seconds instead of 300 milliseconds, and the calling service’s thread pool fills up. Requests queue behind the stalled threads, latency spikes propagate upstream, and within minutes, an entire microservices fleet is degraded. This cascading failure pattern is one of the most common production incidents in distributed systems. Circuit breakers are frequently deployed inside sidecar proxies like Envoy, exactly the deployment vehicle discussed in the previous lesson on the Sidecar pattern.
The Circuit Breaker pattern addresses this failure mode directly. Borrowed from electrical engineering, where a physical breaker trips to prevent a short circuit from burning down a building, the software circuit breaker prevents a system from repeatedly calling a failing dependency. This lesson covers the pattern’s states and transitions, walks through a programmatic implementation, and examines how to monitor and tune circuit breakers in production environments.
The three states of a circuit breaker
The Circuit Breaker pattern operates as a
Three distinct states govern the breaker’s behavior: ...