Presentation at CCGrid 2014

An article summarizing our latest results on resource usage control in multi-tenant applications will be presented at the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) in Chicago, USA. Out of 283 submissions, 54 papers have been accepted as full papers, leading to an acceptance rate of 19%. The paper is one of the results originating from a successful collaboration between SAP and members of the Chair of Software Engineering at the University Würzburg.

Rouven Krebs, Simon Spinner, Nadia Ahmed, and Samuel Kounev. Resource Usage Control In Multi-Tenant Applications. In Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014), Chicago, IL, USA, May 26, 2014. [pdf]

Abstract: 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 the paper, the authors present 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.