Public cloud service vendors provide a surplus of computing resources at a cheaper price as a spot instance. Despite the cheaper price, the spot instance can be forced to be shutdown at any moment whenever the surplus resources are in shortage. To enhance spot instance usage, vendors provide diverse spot instance datasets. Amon them, the spot price information has been most widely used so far. However, the tendency toward barely changing spot price weakens the applicability of the spot price dataset. Besides the price dataset, the recently introduced spot instance availability and interruption ratio datasets can help users better utilize spot instances, but they are rarely used in reality. With a thorough analysis, we could uncover major hurdles when using the new datasets concerning the lack of historical information, query constraints, and limited query interfaces. To overcome them, we develop SpotLake, a spot instance data archive web service that provides historical information of various spot instance datasets. Novel heuristics to collect various datasets and a data serving architecture are presented. Through real-world spot instance availability experiments, we present the applicability of the proposed system. SpotLake is publicly available as a web service to speed up cloud system research to improve spot instance usage and availability while reducing cost.
翻译:公共云服务供应商以更廉价的价格作为现场实例提供大量计算资源。尽管价格更便宜,但当剩余资源短缺时,当场实例随时可能被迫关闭。为了加强现场实例的使用,当场供应商提供各种不同的现场实例数据集。当场价格信息迄今为止被最广泛地使用。然而,当场价格信息趋向于仅仅改变现时价格的趋势削弱了现时价格数据集的适用性。除了价格数据集外,最近推出的现场实例提供和中断比率数据集可以帮助用户更好地利用现时实例,但它们很少在现实中使用。经过彻底分析,当使用关于历史信息缺乏、查询限制和查询界面有限的新数据集时,我们就能发现重大障碍。为了克服这些障碍,我们开发了现场数据存档网络服务SpotLake,即现场数据存档服务,提供各种现时实例数据集的历史信息。除了收集各种数据集和数据服务结构的超常性理论外,还演示了收集各种数据集和数据服务的架构。通过现实世界现场实例提供试验,我们展示了拟议系统的可适用性。我们通过全面分析,可以公开提供网络服务,以降低云层使用率,同时降低成本。