With the growing demand for real-time, scalable, and reliable airline reservation systems, it is essential to provide advanced architectural solutions for modern software development. Existing monolithic architecture is facing challenges to overcome the issue when there is high traffic with accessing data from multiple locations or sources like GDS, LCC and flight APIs. This paper presents a Cloud-Enabled Microservices Architecture (CEMA) for a subsequent-generation online airline reservation systems. The proposed architecture integrates Global Distribution Systems (GDS), Low-Cost Carriers (LCC), and Flight APIs. Which will improve scalability, fault tolerance, and overall performance. By decoupling services including flight search, reserving, fee, and notification, the system allows unbiased scaling and higher aid utilization. During overall performance assessments, the system treated up to 10,000 concurrent users, preserving a median reaction time of 590 ms below peak time load. The flight service provider tested a 45% improvement in response time, lowering latency from 480 ms to 250 ms below minimum load conditions. Failure checking out showed that the system recovered from microservice failures in underneath 200 ms, ensuring high availability. In load testing out, the booking microservice processed 1,000 bookings, consistent with a 95% issuing success rate. Additionally, the architecture executed 99.9% uptime, making sure continuous service shipping even at some point of peak visitors’ periods. The integration of GDS and LCC APIs improved the systems inventory insurance by using 35%, presenting users with a broader selection of flights. This study demonstrates that a microservices-primarily based approach can considerably enhance the efficiency and scalability of online airline reservation systems.