Circuit Breaker Pattern
In a distributed system, services often depend on other services to fulfill requests. A cascading failure occurs when a failure in one service triggers a chain reaction of failures in other dependent services.
Here’s what happens without a circuit breaker:
- Service B Slows Down: A downstream service (e.g., a database or third-party API) becomes slow or unavailable.
- Retry Storm: Service A, which calls Service B, experiences timeouts. It retries the requests, hoping Service B will recover. This flood of retries, known as a retry storm, adds even more load to the already struggling Service B, preventing it from recovering.
- Resource Exhaustion: Service A's resources (like thread pools, memory, and CPU) become consumed by waiting for responses from Service B.
- Failure Spreads: Now that Service A is unresponsive, any service that calls it also begins to fail. The failure ripples through the system, leading to a major outage.
The Circuit Breaker pattern prevents this by stopping the chain reaction at the source.
In this chapter, we will dive deep into the Circuit Breaker pattern, explaining how it works, why it's essential for building resilient microservices, and how you can implement it in your own systems.