How do you ensure data synchronization across microservices in cloud-native applications?

In cloud-native applications, microservices are independently deployable and loosely coupled components, each managing its own dedicated data storage. Data synchronization ensures cross-service data consistency, which is crucial for business reliability, transaction integrity, and real-time operations, such as the coordination scenario between order and inventory services in e-commerce systems.

Core mechanisms include event-driven architecture and message queues (e.g., Kafka or RabbitMQ), utilizing the principle of eventual consistency to avoid complex distributed transactions and reduce blocking. Features include asynchronous communication and patterns like Saga for handling long-running processes, which practically enhance system scalability, elasticity, and fault tolerance, driving designs toward decoupling and high availability.

Implementation steps are as follows: 1. Integrate message brokers to publish and subscribe to events; 2. Apply the Saga pattern to manage transaction sequences; 3. Set up monitoring and compensation measures to handle failures. Typical scenarios include payment process synchronization, with business values including enhanced system agility, reduced operational costs, and mitigated risks of data inconsistency.