Multi-Cloud Data Synchronization Using Kafka Stream Processing Varun Kumar Tambi

In today’s rapidly evolving cloud landscape, enterprises are increasingly adopting multi-cloud strategies to enhance availability, avoid vendor lock-in, and optimize operational costs. However, this architectural shift introduces significant challenges in synchronizing data across heterogeneous cloud platforms in real time. Traditional batch synchronization techniques fail to meet the low-latency and high-throughput demands of modern applications. This paper presents a robust, scalable, and real-time data synchronization architecture leveraging Kafka Stream Processing to ensure consistency and continuity of data across multiple cloud environments.