@inproceedings{22,
  keywords = {automation, Business, cloud computing, cloud services, Databases, deployment and orchestration, domain-specific modeling, knowledge base, Knowledge based systems, Servers, Software, Topology},
  author = {Anirban Bhattacharjee and Yogesh Barve and Aniruddha Gokhale and T. Kuroda},
  title = {A Model-Driven Approach to Automate the Deployment and Management of Cloud Services},
  abstract = {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.},
  year = {2018},
  journal = {2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)},
  pages = {109-114},
  month = {Dec},
}