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Microservices are useful when you need independent scaling, deployment, and clear boundaries in software design.

Dependency failures can disrupt applications, but resilience patterns can help manage them.

Graceful degradation allows apps to function partially during service failures.

Fallbacks allow systems to handle failures safely and maintain user experience.

Crash failures stop a service, while network failures disrupt communication.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Cascading failures occur when one service's failure impacts others, causing widespread issues.

Partial failure means some services fail while others keep running, impacting system reliability.

A Circuit Breaker helps prevent system failures by stopping calls to unhealthy services.

Distributed backpressure helps manage the flow of work between services to prevent overload.

The Circuit Breaker pattern controls service calls to prevent failures from spreading.

A timeout indicates a deadline was exceeded, not necessarily a failure.

Synchronous communication waits for a response, while asynchronous continues without waiting.

Kafka can help ensure messages are processed once, but requires careful design.

RPC allows one service to call a function in another service over the network.

Retry storms occur when too many retries overload a failing service.

gRPC allows efficient communication between services using a structured request-response model.

Fail-stop means a system stops and stays down, while fail-recover means it can come back but needs to be ready.

Backpressure helps manage message flow in Kafka during traffic spikes.