system-design

Distributed systems design involves planning event-driven architectures, caching, queues, and databases with explicit consistency models. It requires analyzing failure tolerance and load balancer strategies to handle distributed failure effectively.

You need an event-driven architecture when designing distributed systems that require asynchronous processing and decoupled services. It helps manage increased traffic by defining event schemas and queue behavior to handle operational complexity and distributed failure.

The best way to plan production reliability is to incorporate circuit breakers, graceful degradation, distributed tracing, and SLOs. Defining health checks and chaos engineering strategies ensures your distributed systems remain observable under failure conditions.

Evaluating microservices vs monolith trade-offs requires analyzing your team size, domain maturity, and operational readiness. This comparison reveals latency and consistency trade-offs, helping you select an architecture that remains maintainable as teams grow.

Limitations of microservices include increased operational complexity and potential latency trade-offs due to network calls. If your team lacks operational readiness, distributed failure handling and consistency models become significantly harder to manage.