This paper addresses the challenge of achieving effective load distribution in information systems operating under dynamic and unpredictable traffic conditions. The study examines traditional static load balancing algorithms, such as Round Robin and Least Connections, and highlights their limitations in adaptive environments. To overcome these constraints, a node rating–based approach is proposed, which dynamically evaluates server states by considering CPU utilization, memory load, and average response time. A comparative simulation of the proposed method against the Least Connections algo- rithm was conducted using a representative request dataset. The results show that the rating-based me- thod mitigates peak loads, enhances system stability, and ensures more efficient resource utilization. Furthermore, the approach demonstrates scalability and suitability for deployment in modern cloud infrastructures.
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