Resource Usage Control in Multi-tenant Applications
Resource Usage Control in Multi-tenant Applications
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DOI：
10.1109/ccgrid.2014.80
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发表时间：
2014-05
期刊：
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通讯作者：
Rouven Krebs;Simon Spinner;nisar. ahmed;Samuel Kounev
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文献类型：
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作者：
Rouven Krebs;Simon Spinner;nisar. ahmed;Samuel Kounev
多租户是一种通过为每个客户提供专用视图，在多个客户中共享一个应用程序实例的方法。 SaaS提供商通常使用这种方法来降低服务提供的成本。租户还期望从他们观察到的绩效方面被隔离，而提供者无法提供绩效保证是潜在云客户的主要障碍。为了确保孤立的绩效，必须控制房客使用的资源。这是一个挑战，因为执行环境的层次负责控制资源使用情况（例如，操作系统），通常没有关于在应用程序级别定义的实体的知识，因此它们无法区分不同的租户。此外，很难预测房客如何通过执行环境的多层传播到物理资源层。来自资源控制层的应用程序的预期抽象不允许仅在应用程序中解决此问题。在本文中，我们提出了一种方法，该方法将资源需求估计技术与基于请求的入学控制结合使用。资源需求估计用于确定各个请求的资源消耗信息。入学控制机制使用这些知识来延迟源自超过其分配资源份额的租户的请求。所提出的方法通过广泛接受的基准标准验证，显示其在当今平台环境动机的设置中的适用性。
Multi-tenancy is an approach to share one application instance among multiple customers by providing each of them a dedicated view. This approach is commonly used by SaaS providers to reduce the costs for service provisioning. Tenants also expect to be isolated in terms of the performance they observe and the providers inability to offer performance guarantees is a major obstacle for potential cloud customers. To guarantee an isolated performance it is essential to control the resources used by a tenant. This is a challenge, because the layers of the execution environment, responsible for controlling resource usage(e.g., operating system), normally do not have knowledge about entities defined at the application level and thus they cannot distinguish between different tenants. Furthermore, it is hard to predict how tenant requests propagate through the multiple layers of the execution environment down to the physical resource layer. The intended abstraction of the application from the resource controlling layers does not allow to solely solving this problem in the application. In this paper, we propose an approach which applies resource demand estimation techniques in combination with a request based admission control. The resource demand estimation is used to determine resource consumption information for individual requests. The admission control mechanism uses this knowledge to delay requests originating from tenants that exceed their allocated resource share. The proposed method is validated by a widely accepted benchmark showing its applicability in a setup motivated by today's platform environments.