An approach to migrations in the container placement task

The article examines the importance of container migration within the context of container placement tasks in cloud data centers. Cloud computing offers organizations significant benefits such as flexibility, scalability, and reduced costs for equipment, energy, and maintenance. Cloud providers face the challenge of not only efficiently placing containers initially but also dynamically reallocating them, along with virtual machines, in response to changing demands and workloads. This necessitates the development and application of migration algorithms. The study analyzes how migration is a critical component for ensuring optimal resource use, maintaining high service availability, and reducing service level agreement (SLA) violations. The research aims to enhance the productivity of cloud data centers in the task of container placement by utilizing container mi-gration algorithms. This objective is driven by the need for cloud providers to use their resources effectively to provide higher quality service and maintain competitive pricing. The use of migrations prevents overloading or underloading of servers and virtual machines, which is especially impor-tant in the highly dynamic environment of cloud computing. The research developed a hybrid mi-gration algorithm that includes the migration of both containers and virtual machines. Mathemati-cal aspects of the container placement task are described, and the migration algorithm is detailed. Experiments showed that implementing this algorithm reduces operational costs by 24% compared to traditional methods that do not use migration, and by 9% compared to less flexible migration strategies. There was also a demonstrated reduction in SLA violation times by 40%, indicating im-provements in service quality and reliability of cloud services. The conclusions of this study confirm that container and virtual machine migration is necessary for effective management of dynamic re-sources in cloud data centers in the context of container placement tasks.