(WIP) CloudCAMP: Automating the Deployment and Management of Cloud Services

Users of cloud platforms often must expend significant manual efforts in the deployment and orchestration of their services on cloud platforms due primarily to having to deal with the high variabilities in the configuration options for virtualized environment setup and meeting the software dependenc...

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Bibliographic Details
Main Authors: Bhattacharjee, Anirban, Barve, Yogesh, Gokhale, Aniruddha, Kuroda, Takayuki
Format: Conference Proceeding
Language:English
Subjects:
Automation
Cloud computing
cloud services
Complexity theory
domain specific modeling
knowledge base
Knowledge based systems
Manuals
orchestration
Software
Online Access:Request full text
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Summary:Users of cloud platforms often must expend significant manual efforts in the deployment and orchestration of their services on cloud platforms due primarily to having to deal with the high variabilities in the configuration options for virtualized environment setup and meeting the software dependencies for each service. Despite the emergence of many DevOps cloud automation and orchestration tools, users must still rely on specifying low-level scripting details for service deployment and management. Using these tools required domain expertise along with a steep learning curve. To address these challenges in a tool-and-technology agnostic manner, which helps promote interoperability and portability of services hosted across cloud platforms, we present initial ideas on a GUI based cloud automation and orchestration framework called CloudCAMP. CloudCAMP uses model-driven engineering techniques to provide users with intuitive and higher-level modeling abstractions that preclude the need to specify all the low-level details. CloudCAMP's generative capabilities leverage a built-in knowledge-base to automate the synthesis of Infrastructure-as-Code (IAC) solution that subsequently can be used to deploy and orchestrate services in the cloud. Preliminary results from a small user study are presented in the paper.
ISSN:2474-2473
DOI:10.1109/SCC.2018.00038