Towards Cognitive Olympic Event Management Systems: AI, Kubernetes, and Intelligent Automation in Mega Sporting Events

Abstract

The rapid digital transformation of global sporting events has significantly increased the demand for intelligent, scalable, and resilient software infrastructures capable of managing complex operational environments. Modern Olympic event management platforms must process massive volumes of real-time data, coordinate distributed services, maintain cybersecurity, and ensure uninterrupted user experiences for athletes, organizers, spectators, and stakeholders. Traditional software management approaches often struggle to meet these dynamic requirements due to limitations in scalability, deployment speed, predictive monitoring, and system adaptability. This study proposes a scalable AI-integrated DevOps architecture designed specifically for smart Olympic event management platforms to address these challenges. The proposed framework combines Artificial Intelligence (AI), DevOps practices, cloud-native technologies, and intelligent automation to enhance operational efficiency, software reliability, and system responsiveness within Olympic digital ecosystems. The architecture incorporates continuous integration and continuous deployment (CI/CD) pipelines, AI-driven predictive analytics, automated infrastructure monitoring, container orchestration, and real-time fault detection mechanisms. Furthermore, the framework utilizes machine learning models to analyse system behaviour, predict potential service disruptions, optimize resource allocation, and support proactive decision-making during large-scale sporting events. This research adopts a design science and system architecture methodology to develop and evaluate the proposed framework through simulated Olympic event management scenarios. Key performance indicators such as deployment frequency, system scalability, incident response time, fault tolerance, and operational efficiency are used to assess the effectiveness of the architecture. The study demonstrates that integrating AI capabilities into DevOps environments can significantly improve software delivery performance, reduce downtime, enhance cybersecurity readiness, and support intelligent event coordination under high-demand operational conditions. The findings contribute to the growing intersection of Software Engineering, intelligent systems, and sports event technologies by providing a novel architectural model for mega-event digital management. The proposed framework offers practical implications for Olympic organizers, smart stadium developers, software engineers, and policymakers seeking to modernize large-scale sporting event infrastructures through advanced automation and intelligent computing technologies. Additionally, the study establishes a foundation for future research in AI-enabled DevOps ecosystems for global event management and smart city applications.