Model Driven Provisioning in Multi-tenant Clouds

A. Gohad, Karthikeyan Ponnalagu, N. Narendra
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引用次数: 15

Abstract

In multi-tenant cloud systems today, provisioning of resources for new tenancy is based on selection from a catalogue published by the cloud provider. The published images are generally a stack of appliances with Infrastructure (IaaS) and Platform (PaaS) layers and optionally Application layers (SaaS). Such a ready-made model enables quicker and streamlined resource provisioning to clients. However, this approach poses certain challenges to clients in the short run and providers in the long run. Unique tenancy requirements from each client are forcibly generalized by selecting one of the available images from the catalogue as the tenancy requirements are not modeled or validated to start with. Moreover, resource provisioning is mostly done towards addressing the peak load expectations in the tenancy. Such a static approach does not help in adapting to dynamically changing tenancy requirements, most often leading to the tenants owning and subsequently paying for more than what they need. In particular, provisioned resources are expected to perform at the same level of quality without accounting for their changing health. In our paper, we propose an extensible dynamic provisioning framework to address these challenges. We start with defining a Tenancy Requirements Model (TRM) which helps map provisioned resources with tenants. The provisioned and candidate resources are also modeled with their Quality of Service (QoS) characteristics which we call Health Grading Model (HGM); this helps in continuous monitoring and grading of resources based on health parameters and enables health prediction for future provisioning. Together, TRM and HGM allow dynamic re-provisioning for existing tenants based on either changing tenancy requirements or health grading predictions. We also present algorithms for prediction based provisioning and tenancy requirement matching. We illustrate our ideas throughout this paper with a running example, and present a proof-of-concept prototype implementation on IBM's Rational Software Architect modeling tool.
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多租户云中的模型驱动配置
在当今的多租户云系统中,为新租户提供资源是基于从云提供商发布的目录中进行选择。发布的映像通常是具有基础设施(IaaS)和平台(PaaS)层以及可选的应用程序层(SaaS)的设备堆栈。这样一个现成的模型可以更快、更精简地向客户端提供资源。然而,这种方法在短期内会给客户带来一定的挑战,在长期内会给供应商带来一定的挑战。由于一开始没有对租赁需求进行建模或验证,因此通过从目录中选择一个可用映像来强制概括每个客户机的唯一租赁需求。此外,资源配置主要是为了解决租户中的峰值负载预期。这种静态方法无助于适应动态变化的租赁需求,通常会导致租户拥有并随后支付超出其需求的费用。特别是,预期所提供的资源将以相同的质量水平运行,而无需考虑其不断变化的运行状况。在我们的论文中,我们提出了一个可扩展的动态供应框架来解决这些挑战。我们首先定义一个租户需求模型(Tenancy Requirements Model, TRM),它有助于将已供应的资源映射到租户。预备资源和候选资源也用它们的服务质量(QoS)特征建模,我们称之为健康分级模型(HGM);这有助于根据运行状况参数对资源进行持续监控和分级,并支持对未来供应进行运行状况预测。TRM和HGM一起允许根据不断变化的租户需求或健康等级预测为现有租户动态重新配置。我们还提出了基于预测的供应和租赁需求匹配算法。在本文中,我们用一个运行的示例来说明我们的想法,并在IBM的Rational Software Architect建模工具上展示了一个概念验证原型实现。
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