Interactive Streamlit-based Simulator for Cloud Simulation and Resource Management

This paper presents the design and evaluation of an interactive cloud simulation platform developed using the Streamlit framework to facilitate real-time experimentation with resource allocation strategies in a virtualized cloud environment. The system enables users to configure CPU, memory, and storage pools through JSON files, define virtual machine (VM) parameters, and evaluate the performance of two scheduling algorithms—Round-Robin and Dynamic Resource-Aware—under light, moderate, and heavy workloads. Real-time dashboards provide visual monitoring of resource usage, VM status, and fault recovery processes. Comparative results demonstrate that the Dynamic Resource-Aware scheduler achieves higher CPU and memory utilization, reduced fault events, and faster recovery times compared to Round-Robin. The simulator’s modular architecture supports extensibility, allowing integration of additional scheduling policies, predictive models, and real-time data streams from IoT or containerized environments. Designed for both academic and research applications, this platform bridges the gap between theoretical models and practical deployment scenarios, offering a controlled and cost-effective environment for studying cloud orchestration strategies.