Optimizing Airline Reservation Systems With Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsiveness

The complexity of airline reservation systems demands solutions that are fast and adaptive in nature. The paper proposes a theoretical framework that deploys edge computing microservices to support the traditional centralized systems, particularly targeting latency and performance issues. Performing calculations like seat inventory checks, bookings, and confirmations closer to the user reduces response time and enhances performance. Kubernetes is a core microservice orchestration system, Kafka handles real-time messaging, while Prometheus and Grafana monitor the resources. This ensures low latency and high throughput, thus enhancing user experience. Additionally, the system is designed to scale seamlessly under peak traffic conditions. A further advantage of this framework is that it is cost-effective in terms of infrastructure establishment and supports emerging technologies like Artificial Intelligence and the Internet of Things, assisting the airline industry and real-time domains such as supply chain management, healthcare, and smart cities. The feasibility of the framework is studied using simulated real-life airline reservation scenarios. The simulation results reveal a latency reduction of up to 60%, throughput improvement of 20-25%, and user satisfaction upsurge of 25%. Edge distribution also enhances reliability by potentially reducing recovery time by more than 30%, while being cost-effective with operational utility cuts of around 15-20%. This architecture, therefore, stands as one practical and extendable solution for airline reservation systems refurbishment and beyond.