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Abstract
The article focuses on the development of an integrated methodological approach to survey the properties of cloud platforms, which includes analyzing load dynamics, monitoring the utilization of CPU and network resources, and identifying application performance bottlenecks. The implementation includes the stages of data collection using standard monitoring tools, data pre-processing and analysis to identify optimal resource allocation strategies. The research of article includes physical validation of cloud infrastructures, performance evaluation on several key metrics such as CPU utilization and network latency, I/O operations, and throughput. The results reveal the potential to improve the performance of such applications by optimizing cloud resource configurations and implementing auto-scaling strategies. The practical significance of article lies in proposing recommendations for cloud resource management that can be used in real-world operational environments. This includes adapting configurations to changing workloads, improving quality of service and reducing the cost of operating cloud systems. The results of the survey can be applied in various industries such as finance, healthcare and education where cloud technology plays a key role.
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