As a popular technique in cloud computing, multi-tenancy (MT) can significantly ease software maintenance, and improve resource utilization. To make use of the MT technique, an application may need to be transformed to be MT-enabled. This process involves finding and processing a special kind of data entities named global isolation points (GIPs). Practically, finding all GIPs of an application is challenging. Traditional method involves manually browsing the application code, requiring a great deal of human effort. To solve this problem, we introduce a toolkit named Auto-MT to help find and process GIPs of an application. Auto-MT is able to find new GIPs based on their relations to known GIPs. To characterize the relation, a novel graph called value flow graph (VFG) is introduced, which models the value flows of data entities. It can also be used in other scenarios, like taint analysis. We have implemented Auto-MT as an Eclipse Plug-in, and applied it to transform Roller, a widely used Java application. Experimental results show that Auto-MT saves substantial human effort, and accelerates the process of transforming applications to be MT-enabled.

Analytical solutions are considered as increasingly important for modern enterprises. Currently, systematical adoption of analytical solutions is limited to only a small set of large enterprises, as the deployment cost is high due to high performance hardware requirement and expensive analytics software. Moreover, such on-premises solutions are not suitable for the occasional analytics consumers. In order to accelerate the prevalence of analytical solutions, this paper explores the feasibility of leveraging SaaS (Software-as-a-Service) delivery model to provide analytics capabilities as services in a cost-effective way. The main contributions of our work include: (1) proposing a framework to enable enterprise tenants to consume analytics capabilities as services; (2) developing a method to enhance existing analytics platform to support multi-tenancy so that a single software instance can effectively support multiple concurrent tenants; (3) designing an SLA (Service Level Agreement) customization mechanism to satisfy the diverse analytics capability demands of tenants. A prototype system has been developed to evaluate the feasibility of our approach.