BUILDING A HIGHLY RESILIENT SYSTEM FOR PROCESSING BILLIONS OF EVENTS DAILY

Abstract

This article presents a comprehensive architectural approach for building a highly resilient system capable of processing 5-10 billion events daily. In response to the exponential growth of data generation across industries, we explore the design principles and technologies required to handle massive-scale event ingestion, real-time processing, and complex analytics. The article details the implementation of a solution utilizing managed services, microservices architecture, and cloud-native data warehousing, addressing key challenges such as scalability, low latency, fault tolerance, and cost-efficiency. We discuss the critical role of Infrastructure as Code (IaC) in maintaining consistency and enabling rapid scaling. The article also covers robust testing methodologies and performance validation strategies essential for ensuring system reliability at scale. By sharing real-world performance metrics and lessons learned, this article provides valuable insights for organizations aiming to build next-generation data processing systems that can drive real-time decision-making and maintain competitiveness in the data-driven economy. This revised abstract provides a more condensed overview of the article's content, touching on the key points without duplicating the detailed information presented in the introduction. It emphasizes the paper's focus on architectural solutions, implementation strategies, and practical insights for building high-volume event processing systems.