Abstract
This paper examines an approach to building an event-driven serverless architecture for a distributed information system operating under uneven and peak load conditions. Modern digital services are characterized by sharp fluctuations in the intensity of incoming requests, which requires maintaining operational stability, acceptable response times, and the ability to quickly scale computing resources. Traditional monolithic and container-based solutions in such environments often require upfront capacity reservations or respond to load surges with delays. The goal of this study is to develop and experimentally evaluate an architectural solution in which request processing is organized as a stream of independent events using a serverless computing model. To this end, a formalized event model and input load generation scheme are proposed, enabling the reproduction of both normal operating modes and short-term peak impacts. The effectiveness was assessed based on a series of controlled computational experiments under various load scenarios. The key metrics used were average processing latency, the p95 metric, system throughput, and the error rate during periods of increased activity. The results obtained during the study demonstrate that as the load increases, the increase in latency is manageable, and the system maintains operability during short-term overloads. This allows us to consider the proposed approach as a promising solution for scalable distributed services.