Enabling Real-Time Transaction Processing in Distributed Cloud Systems: Architectural, Operational, and Societal Dimensions
TL;DR
Using empirical benchmarks and advancements made in cloud computing technology and scheduling, this article investigates the architectural approaches, infrastructure optimization methods, and performance techniques that contribute to enabling high throughput and energy efficiency in transactional systems operating in real time.
Abstract
Real-time transaction processing has emerged as a foundational requirement of modern digital economies, underpinning payment networks, trading platforms, and fraud-detection systems that collectively handle trillions of dollars in daily transaction volume. As cloud-native architectures displace monolithic legacy systems, organizations face a dual imperative: delivering consistently sub-millisecond latency at global scale while simultaneously reducing the energy footprint of the infrastructure that sustains these workloads. Systems distributed across clouds using the architecture based on microservices, event-driven pipelines, containerization, and intelligent orchestration have been shown to be able to meet both requirements, although the engineering considerations that go into making this possible have not been extensively studied in the literature. This article investigates the architectural approaches, infrastructure optimization methods, and performance techniques that contribute to enabling high throughput and energy efficiency in transactional systems operating in real time. Using empirical benchmarks and advancements made in cloud computing technology and scheduling, the article further analyzes the social consequences of adopting such a system, including financial inclusion, sustainability, and trust.