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Expressive data storage policies for multi-cloud storage configurations

机译:多云存储配置的高效数据存储策略

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摘要

Software-as-a-Service (SaaS) providers increasingly rely on multi-cloud setups to leverage the combined benefits of different enabling technologies and third-party providers. Especially, in the context of NoSQL storage systems, which are characterized by heterogeneity andquick technological evolution, adopting the multi-cloud paradigm is a promising way to deal with different data storage requirements. Existing data access middleware platforms that support this type of setup (polyglot persistence) commonly rely on (i) configuration models that describe the multi-cloud setup, and (ii) the hard-coded logic in the application source code or the data storage policies that define how the middleware platforms should store data across different storage systems. In practice, however, both models are tightly coupled, i.e. the hard-coded logic in the application source code and data storage policies refer to specific configuration model elements, leads to fragility issues (ripple effects) and hinders reusability. Especially in multi-cloud configurations that change often (e.g., in dynamic cloud federations), this is a key problem.In this paper, we present a more expressive way to specify storage policies, that involves (i) enriching the configuration models with metadata about the technical capabilities of the storage systems, (ii) referring to the desired capabilities of the storage system in the storage policies, and (iii) leaving actual resolution to the policy engine. Our validation in the context of a realistic SaaS application shows how the policies accommodate such changes for a number of realistic policy change scenarios. We also evaluate the performance impact in order to investigate the performance overhead of our approach. The results demonstrate that an application can benefit from an expressive data storage policy while incurring a minimal performance overhead of less than 2 %.
机译:软件即服务(SaaS)提供商越来越依赖于多云设置来利用不同支持技术和第三方提供商的综合利益。特别是在以异质性和技术快速发展为特征的NoSQL存储系统的背景下,采用多云范式是解决不同数据存储需求的一种有前途的方法。支持这种设置(多语言持久性)的现有数据访问中间件平台通常依赖于(i)描述多云设置的配置模型,以及(ii)应用程序源代码或数据存储策略中的硬编码逻辑定义中间件平台应如何在不同存储系统之间存储数据。但是实际上,这两个模型是紧密耦合的,即,应用程序源代码和数据存储策略中的硬编码逻辑引用特定的配置模型元素,从而导致脆弱性问题(波纹效应)并阻碍了可重用性。尤其是在经常更改的多云配置中(例如,在动态云联盟中),这是一个关键问题。在本文中,我们提出了一种更具表现力的方式来指定存储策略,其中包括(i)使用元数据来丰富配置模型关于存储系统的技术功能,(ii)在存储策略中引用存储系统的所需功能,并且(iii)将实际解决方案留给策略引擎。我们在实际SaaS应用程序上下文中的验证表明,在许多实际的策略更改方案中,策略如何适应此类更改。我们还评估了性能影响,以调查我们方法的性能开销。结果表明,应用程序可以从富有表现力的数据存储策略中受益,同时将性能开销降至2%以下。

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