Event-Driven Cloud Architectures for Real-Time Data Processing

Abstract

Real-time data processing has emerged as a cornerstone of modern cloud applications, necessitating innovative architectural designs. This paper presents an event-driven cloud architecture tailored for handling dynamic workloads and high-throughput data streams. By leveraging serverless computing, asynchronous communication protocols, and distributed message brokers, the architecture achieves unparalleled responsiveness and scalability. Comparative evaluations illustrate its superiority over traditional architectures in terms of latency, throughput, and fault resilience. The findings underscore the critical role of event-driven paradigms in addressing the challenges of real-time data-intensive applications within cloud environments.