Understanding fault tolerance in distributed systems

Fault tolerance is crucial in distributed applications, ensuring systems continue to operate despite failures such as hardware breaks, software bugs, or network issues. It minimizes disruptions and maintains service availability, thereby preserving user trust and preventing migration to competitors. Fault tolerance involves strategies like redundancy, data replication, failover mechanisms, and graceful degradation. While often confused with high availability, fault tolerance emphasizes seamless operation despite component failures. Designing fault-tolerant systems requires balancing cost, performance, and recovery time objectives, while addressing challenges like data consistency and network partitioning. Cloud platforms such as AWS, Google Cloud, and Azure provide inherent fault tolerance features, but developers must still handle application-level resilience. Tools like Temporal simplify this process by managing state and automating retries, supporting reliable workflows. In real-world applications, fault tolerance can be seen in banking, e-commerce, and logistics, where it prevents downtime and maintains operational resilience.