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Artificial Intelligence based BOT to Manage and Administer Cloud Services
Author(s) -
P. Z Muzzamil
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.35367
Subject(s) - cloud computing , computer science , suite , process (computing) , resource (disambiguation) , workspace , resource management (computing) , world wide web , knowledge management , artificial intelligence , operating system , distributed computing , computer network , archaeology , robot , history
In the era of cloud computing, every company uses cloud technology for its applications and other infrastructure to provide a highly available and easily accessible user experience. While monitoring and managing these assets becomes a hectic work for the IT admins. On which the Level of Effort (LOE) of the resource allocated will be high and the resource must reach different console for different information. Introducing an AI-powered bot which can monitor and manage the cloud assets will reduce the manpower drastically. Most enterprises currently have very rudimentary systems of resource management where someone in the role of an Azure or resource administrator log on to the Admin Portal of their resources and have to apply filters and search through multiple screens to find even the most basic information regarding utilization and cost. This leads to inefficient management of resources and almost leads to overspending in resources that are being underutilized. The implementation of the project will involve creating a cloud services management bot that can be integrated with an enterprise’s collaboration suite as a way to enhance the enterprise’s modern workspace. The bot is to be trained on a set of query data as part of the artificial intelligence process using the natural language processing packages that are included in the Azure Cognitive Services suite. Once queries are processed, the system will connect with the respective endpoints of the Azure Resource Management REST APIs to retrieve relevant resource utilization information and show that to the end-user.

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