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Tier-Centric Resource Allocation in Multi-Tier Cloud Systems

机译:多层云系统中以层为中心的资源分配

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In IT service delivery and support, the cloud paradigm has introduced the problem of resource over-provisioning through rapid automation (or orchestration) of manual IT operations. Due to the elastic nature of cloud computing, this shortcoming ends up significantly reducing the real benefit, viz., the cost-effectiveness of cloud adoption for Cloud Service Consumers (CSC). Similarly, detecting and eliminating such over-provisioning of cloud resources without affecting the quality of service (QoS) is extremely difficult for Cloud Service Providers (CSPs) since they have visibility only into the state of the IT services (cloud resources) but none into the actual performance of business services. In this paper, we propose Tier-centric Business Impact and Cost Analysis (T-BICA), a tier-centric optimal resource allocation algorithm, to address the problem of rapid provisioning of IT resources in modern enterprise cloud environments, through extensive data gathering and performance analyses of business services in a simulated environment emulating a mature cloud service provider. We have derived improved analytics to address the issues and to accelerate real cloud adoption for large enterprises within the context of meeting (or exceeding) business service level objectives (SLOs) and minimizing the cloud subscription cost (OpEx) for the business. While investigating the problem, we consider the time and the cost of delivering business service in medium- to large-size enterprise environments, quantifying the negative impact of IT resource over-provisioning (due to highly mature IT services centric orchestration capabilities) on the business, and indicate how the suggested cloud analytics could assist in reducing total cost of ownership (TCO) of the business service. From our analysis of the test data, we have observed that our suggested approach and analytic reduces the cost of delivering business services by 65.19 percent, and improves the performance (total time to deliver) by 74.18 percent when compared to the existing modern cloud management and resource provisioning approach. Using T-BICA dramatically reduces upfront costs (CapEx) for CSPs (from the capacity procurement and management points of view) through efficient on-demand resource de-provisioning, without affecting business SLOs and IT service level agreements (SLAs). The improved dynamic allocation of resources also makes for better efficiency of utilization, which in turn has desirable consequences for sustainability, and makes this an approach for “Green” IT.
机译:在IT服务交付和支持中,云范式通过手动IT操作的快速自动化(或编排)引入了资源过度配置的问题。由于云计算的弹性,这种缺点最终会大大降低实际收益,即云服务消费者(CSC)采用云的成本效益。同样,对于云服务提供商(CSP)来说,检测和消除云资源的这种超额配置而不影响服务质量(QoS)极其困难,因为它们只能看到IT服务(云资源)的状态,而无法看到商业服务的实际表现。在本文中,我们提出了以层为中心的业务影响和成本分析(T-BICA),这是一种以层为中心的最佳资源分配算法,旨在通过广泛的数据收集和处理来解决现代企业云环境中快速配置IT资源的问题。在模拟环境中模拟成熟的云服务提供商的业务服务的性能分析。我们已经开发出改进的分析方法来解决问题,并在满足(或超过)业务服务水平目标(SLO)并最大程度地降低业务的云订阅成本(OpEx)的背景下,为大型企业加速实际云的采用。在调查问题时,我们考虑了在中型到大型企业环境中交付业务服务的时间和成本,量化了IT资源超额配置(由于高度成熟的以IT服务为中心的编排能力)对业务的负面影响,并指出建议的云分析如何帮助降低业务服务的总拥有成本(TCO)。通过对测试数据的分析,我们发现,与现有的现代云管理相比,我们建议的方法和分析将交付业务服务的成本降低了65.19%,并将性能(交付总时间)提高了74.18%。资源供应方法。使用T-BICA(通过容量采购和管理的观点),通过有效的按需资源预配置,可以大大降低CSP的前期成本(CapEx),而不会影响业务SLO和IT服务水平协议(SLA)。改进的资源动态分配还可以提高利用率,这反过来又对可持续性产生了理想的影响,并使之成为“绿色” IT的一种方法。

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