The problem of using cloud computing resources for services is related to planning the amount of resources needed and their subsequent reservation. This problem occurs both on the side of the customer who tries to minimize the cost of the service and on the side of the cloud provider who wants to make the best use of existing infrastructure without introducing any modifications. In our article, we want to show how the problem of overestimating the utilization of resources for services which use cloud computing can be handled. Solving this problem will allow significant savings to be made by both the customer and the cloud infrastructure provider. The system we have developed demonstrates the considerable utility of machine learning methods when planning cloud resource reservation for network services. The models proposed, which use a multilayer perceptron, have yielded good results for both short- and long-term reservations.

将云计算资源用于服务的问题与计划所需的资源量及其后续预留有关。在试图使服务成本最小化的客户方面和希望在不进行任何修改的情况下充分利用现有基础架构的云提供商方面，都会出现此问题。在我们的文章中，我们想展示如何解决高估使用云计算的服务的资源利用率的问题。解决此问题将使客户和云基础架构提供商都可以节省大量资金。我们开发的系统演示了在规划网络服务的云资源预留时机器学习方法的巨大实用性。提出的模型