How do cloud-native applications handle data replication and consistency?

Cloud-native applications handle data replication and consistency in distributed environments by replicating data to multiple nodes or regions to ensure high availability, fault tolerance, and elasticity. They are suitable for microservice architectures such as financial payment systems or multi-region deployment scenarios to avoid single points of failure and enhance business continuity.

Their core is based on consensus protocols like Raft or Paxos to coordinate write operations, supporting eventual consistency models to reduce latency or strong consistency to ensure atomicity. In practical applications, databases such as Cassandra or TiDB are combined with Kubernetes StatefulSets to manage replica synchronization, ensuring uninterrupted service operation and addressing the risk of node failures, thereby simplifying operational complexity.

Implementation steps include selecting database configurations (e.g., PostgreSQL streaming replication) and using controllers in Kubernetes to automatically scale replicas. A typical application is e-commerce order systems to prevent data loss. The business value lies in improving data reliability, reducing downtime costs, enhancing user experience, and supporting global expansion.