Event-Driven Architectures for Real-Time Data Synchronization: Lessons from Multi-Region Cloud Deployments

Abstract

The current paper examines the role of event-driven architectures (EDA) to assist in ensuring the synchronization of real-time data in various locations of the cloud. The current global systems have numerous challenges such as delays in information, duplicate and regional interruptions in case information is modified at various points simultaneously. This work is created with the help of AWS serverless primaries (Lambda, Kinesis, DynamoDB Streams) and provides an event-driven model of synchronization that manages millions of users.

The experiment is an analysis of the latency, throughput, and error rates over the regions in the process of live replication. It further verifies idempotence event handling and cross region restoration during the event of failures. Findings indicate that pipelines supported by an event can continue with low latency rates, high availability, and a proper level of replication regardless of network failures. There are also quantitative results, small code samples, and specific visualization charts of the paper to explain the behavior of the system in a clear manner. Production-grade implementations are tweaked into lessons that can be generalized into a blueprint that can be implemented in other enterprises. This study can be used to construct stronger, smoother, and non-conformist data pipelines when using a distributed cloud system.