Session abstract
What you’ll learn
Modern systems rarely keep all their data in one place anymore. Data may sit across AWS, Azure, GCP, private cloud, SaaS platforms, and internal databases. The hard part is not just moving the data. The hard part is keeping it consistent when each environment has different APIs, different latency, different failure behavior, and different security requirements. This session presents a three-layer architecture for real-time multi-cloud synchronization, based on my published article, “A Conceptual Model for Real-Time Data Synchronization in Multi-Cloud Environments.” The architecture separates the problem into three parts: data acquisition, synchronization orchestration, and application access. That separation matters because ingestion, consistency control, conflict handling, encryption, and read access should not all be mixed into one fragile pipeline. The talk focuses on the engineering decisions behind the model. It covers event-driven synchronization for faster propagation, conflict detection for concurrent updates, hybrid encryption for protecting synchronized data, and audit logging for traceability across cloud boundaries. It also discusses simulation-based findings from the paper, including improvements in latency, consistency, and security under tested multi-cloud scenarios. Attendees will leave with a practical way to think about multi-cloud synchronization design: how to structure the workflow, where to handle conflicts, how to protect data as it moves between environments, and how to keep the system auditable. Examples from finance, healthcare, and e-commerce will show why real-time consistency, secure synchronization, and traceability matter when downstream systems depend on accurate data.