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Алгоритм автоматического масштабирования дискового пространства в системе оркестрации Kubernetes

выпускная квалификационная работа магистра

Алгоритм автоматического масштабирования дискового пространства в системе оркестрации Kubernetes

Abstract

В данной работе предлагается алгоритм автоматического масштабирования персистентных томов в системе оркестрации контейнеров — Kubernetes. Автомасштабирование означает уменьшение/увеличение целевых ресурсов в зависимости от некоторой нагрузки. В случае горизонтального масштабирования томов мы изменяем количество томов, а в вертикальном случае мы изменяем размер каждого тома. Также мы вводим смешанное масштабирование, которое включает как горизонтальное, так и вертикальное в качестве подэтапов для достижения желаемого состояния. Предлагается выбирать из вышеперечисленных способов исходя из свободной емкости хранилища кластера Kubernetes и его узлов. Подходы, описанные в статье, позволяют эффективно использовать ресурсы постоянного хранилища без ручного взаимодействия с кластером Kubernetes.

The paper describes a proposal of an algorithm for Persistent Volumes auto-scaling in a container orchestration system – Kubernetes. Auto-scaling stands for decreasing/increasing target resources depending on some load. In case of horizontal Volumes scaling, we vary the number of Volumes, while in the vertical case we vary the size of each Volume. Also, we introduce mixed scaling that includes both: horizontal and vertical as sub steps to reach a desired state. It is proposed to choose from the methods above based on free storage capacity of Kubernetes cluster and its nodes. Approaches described in the article allow to use persistent storage resources in an efficient way without manual interaction with Kubernetes cluster.

Keywords

горизонтальное масштабирование, storage, persistent volume, персистентный том, auto-scaling, vertical scaling, Информационные Ñ‚ÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸Ð¸, автомасштабирование, Алгоритмы, horizontal scaling, вертикальное масштабирование, Ñ Ñ€Ð°Ð½Ð¸Ð»Ð¸Ñ‰Ðµ

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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