6 research outputs found

    Implementing the required degree of multitenancy isolation : a case study of cloud-hosted bug tracking system

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    Implementing the required degree of isolation between tenants is one of the significant challenges for deploying a multitenant application on the cloud. In this paper, we applied COMITRE (COmponent-based approach to Multitenancy Isolation Through request RE-routing) to empirically evaluate the degree of isolation between tenants enabled by three multitenancy patterns (i.e., shared component, tenant-isolated component, and dedicated component) for a cloud-hosted Bug tracking system using Bugzilla. The study revealed among other things that a component deployed based on dedicated component offers the highest degree of isolation (especially for database transactions where support for locking is enabled). Tenant isolation based on performance (e.g., response time) favoured shared component (compared to resource consumption (e.g., CPU and memory) which favoured dedicated component). We also discuss key challenges and recommendations for implementing multitenancy for application components in cloud-hosted bug tracking systems with guarantees for isolation between multiple tenants

    Evaluating degrees of tenant isolation in multitenancy patterns : a case study of cloud-hosted Version Control System (VCS)

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    One of the key concerns of implementing multitenancy (i.e., serving multiple tenants with a single instance of an application) on the cloud is how to enable the required degree of isolation between tenants, so that the required performance of one tenant does not affect other tenants. There is little research which provides empirical evidence on the required degree of isolation between tenants under different cloud deployment conditions. This paper applies COMITRE (COmponent-based approach to Multitenancy Isolation Through request RE-routing) to empirically evaluate the degree of isolation between tenants enabled by multitenancy patterns for cloud-hosted Version Control System (VCS). We implemented three multitenancy patterns (i.e., shared component, tenant-isolated component, and dedicated component) by developing a multitenant component using the FileSystem SCM plugin integrated within Hudson. The study revealed that dedicated component provides the highest degree of isolation between tenants (compared to shared component and tenant-isolated component) in terms of error% (i.e., the percentage of errors with unacceptably slow response times) and throughput. System load of tenants showed no variability, and hence did not influence the degree of tenant isolation for all the three multitenancy patterns. We also provide some recommendations to guide an architect in implementing multitenancy isolation on similar VCS tools like Subversion and CVS

    Degrees of tenant isolation for cloud-hosted software services : a cross-case analysis

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    A challenge, when implementing multi-tenancy in a cloud-hosted software service, is how to ensure that the performance and resource consumption of one tenant does not adversely affect other tenants. Software designers and architects must achieve an optimal degree of tenant isolation for their chosen application requirements. The objective of this research is to reveal the trade-offs, commonalities, and differences to be considered when implementing the required degree of tenant isolation. This research uses a cross-case analysis of selected open source cloud-hosted software engineering tools to empirically evaluate varying degrees of isolation between tenants. Our research reveals five commonalities across the case studies: disk space reduction, use of locking, low cloud resource consumption, customization and use of plug-in architecture, and choice of multi-tenancy pattern. Two of these common factors compromise tenant isolation. The degree of isolation is reduced when there is no strategy to reduce disk space and customization and plug-in architecture is not adopted. In contrast, the degree of isolation improves when careful consideration is given to how to handle a high workload, locking of data and processes is used to prevent clashes between multiple tenants and selection of appropriate multi-tenancy pattern. The research also revealed five case study differences: size of generated data, cloud resource consumption, sensitivity to workload changes, the effect of the software process, client latency and bandwidth, and type of software process. The degree of isolation is impaired, in our results, by the large size of generated data, high resource consumption by certain software processes, high or fluctuating workload, low client latency, and bandwidth when transferring multiple files between repositories. Additionally, this research provides a novel explanatory framework for (i) mapping tenant isolation to different software development processes, cloud resources and layers of the cloud stack; and (ii) explaining the different trade-offs to consider affecting tenant isolation (i.e. resource sharing, the number of users/requests, customizability, the size of generated data, the scope of control of the cloud application stack and business constraints) when implementing multi-tenant cloud-hosted software services. This research suggests that software architects have to pay attention to the trade-offs, commonalities, and differences we identify to achieve their degree of tenant isolation requirements

    Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation

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    One of the challenges of deploying multitenant cloud-hosted services that are designed to use (or be integrated with) several components is how to implement the required degree of isolation between the components when there is a change in the workload. Achieving the highest degree of isolation implies deploying a component exclusively for one tenant; which leads to high resource consumption and running cost per component. A low degree of isolation allows sharing of resources which could possibly reduce cost, but with known limitations of performance and security interference. This paper presents a model-based algorithm together with four variants of a metaheuristic that can be used with it, to provide near-optimal solutions for deploying components of a cloud-hosted application in a way that guarantees multitenancy isolation. When the workload changes, the model based algorithm solves an open multiclass QN model to determine the average number of requests that can access the components and then uses a metaheuristic to provide near-optimal solutions for deploying the components. Performance evaluation showed that the obtained solutions had low variability and percent deviation when compared to the reference/optimal solution. We also provide recommendations and best practice guidelines for deploying components in a way that guarantees the required degree of isolation
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