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A Model-Driven Approach to Automate the Deployment and Management of Cloud Services

机译:一种模型驱动的方法来自动化云服务的部署和管理

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Although many provisioning tools are available for deployment and management of composite cloud services to overcome the manual efforts that are tedious and error-prone, users are often required to specify Infrastructure-as-Code (IAC) solutions via low-level scripting. IAC demands domain knowledge for provisioning the services across heterogeneous cloud platforms and incurs a steep learning curve. To address these challenges, we present a technology-and platform-agnostic self-service framework called CloudCAMP. It incorporates domain-specific modeling so that the specifications and dependencies imposed by the cloud platform and application architecture can be specified at an intuitive, higher level of abstraction without the need for domain expertise. CloudCAMP transforms the partial specifications into deployable Infrastructure-as-Code (IAC) using the Transformational-Generative paradigm and by leveraging an extensible and reusable knowledge base. The auto-generated IAC can be handled by existing tools to provision the services components automatically. We validate our approach quantitatively by showing a comparative study of savings in manual and scripting efforts versus using CloudCAMP.
机译:尽管可以使用许多配置工具来部署和管理复合云服务,以克服繁琐且容易出错的手动工作,但通常仍要求用户通过低级脚本来指定基础架构即代码(IAC)解决方案。 IAC需要跨领域的知识,才能在异构云平台之间提供服务,并导致学习曲线陡峭。为了解决这些挑战,我们提出了一种与技术和平台无关的自助服务框架,称为CloudCAMP。它结合了特定领域的建模,因此可以在不需要领域专业知识的情况下,以直观,更高的抽象级别指定云平台和应用程序体系结构所施加的规范和依赖性。 CloudCAMP使用“转换生成”范式并利用可扩展和可重用的知识库,将部分规范转换为可部署的基础架构即代码(IAC)。自动生成的IAC可以使用现有工具进行处理,以自动设置服务组件。通过展示与使用CloudCAMP相比节省人工和脚本工作的对比研究,我们定量地验证了我们的方法。

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