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Causality in distributed systems helps understand how events influence each other, beyond just timestamps.

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

Graceful degradation allows apps to function partially during service failures.

Lamport Timestamps help order events in distributed systems while preserving causality.

In distributed systems, timestamps don't always reflect the true order of events.

Vector clocks help track the order and concurrency of events in distributed systems.

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

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

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

Physical time tells when events happen, while logical time tells their order.

Apache Kafka is a system for managing large volumes of events efficiently.

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

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

Observability helps engineers understand system behavior to debug production issues effectively.

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

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

Backpressure helps manage message flow in Kafka during traffic spikes.

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

Idempotency ensures that repeated operations in APIs do not cause duplicate effects.

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

Network partitions occur when servers are operational but can't communicate, affecting system performance.

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

The CAP Theorem explains the trade-offs in distributed systems during network failures.

Message delivery semantics define how messages are sent in distributed systems and handle failures.