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.

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云托管软件服务的租户隔离度：跨案例分析

在云托管的软件服务中实现多租户时，一个挑战是如何确保一个租户的性能和资源消耗不会对其他租户产生不利影响。软件设计师和架构师必须为其选定的应用程序需求实现最佳程度的租户隔离。这项研究的目的是揭示在实现所需程度的租户隔离时需要权衡的因素，共同点和差异。这项研究使用对选定的开源云托管软件工程工具的跨案例分析，以经验评估租户之间的不同隔离度。我们的研究揭示了案例研究中的五个共性：减少磁盘空间，使用锁定，低云资源消耗，自定义和使用插件架构，以及多租户模式的选择。这些常见因素中的两个损害了租户隔离。如果没有减少磁盘空间的策略并且没有采用自定义和插件架构，则会降低隔离度。相反，当仔细考虑如何处理高工作负载，使用数据和进程锁定来防止多个租户之间发生冲突以及选择适当的多租户模式时，隔离度会提高。该研究还揭示了五个案例研究差异：生成数据的大小，云资源消耗，对工作负载变化的敏感性，软件过程的影响，客户端延迟和带宽以及软件过程的类型。根据我们的结果，隔离程度会因生成的数据量过大而受到损害，在存储库之间传输多个文件时，某些软件进程会占用大量资源，工作量或波动很大，客户端延迟很短，并且带宽很大。此外，这项研究为（i）将租户隔离映射到不同的软件开发过程，云资源和云堆栈层提供了新颖的解释框架；（ii）解释在实现时考虑影响租户隔离的不同权衡因素（即资源共享，用户/请求数量，可定制性，生成的数据大小，云应用程序堆栈的控制范围和业务约束）多租户云托管软件服务。这项研究表明，软件架构师必须注意权衡，通用性，