Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 7 No 10 (2023): Volume 7, Issue 10, October 2023 | Pages: 282-289
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 30-10-2023
Ensuring the best performance of a Windows Server system is critical for businesses since any operational failures may result in significant financial losses. Considering this, the use of automated mistake resolution solutions appears as a proactive technique for dealing with prospective concerns. This study provides a ground-breaking technique specialized for Windows Server settings, consisting of three essential pieces deliberately intended to identify and control faults. A thorough examination of the first factor, Predictive Errors, necessitates a thorough examination of server performance data. By studying this data, the system may proactively detect locations where problems may occur. This foresight allows the system to take preventive steps, eventually reducing downtime and improving overall server performance. The second component, the Automated Error Resolution module, uses scripts and automated procedures to correct mistakes that occur. Notably, this module allows for the inclusion of human operators in the resolution process when necessary, guaranteeing a balanced and successful approach. Configuration Management is critical in preserving the server environment's accuracy. It manages the tracking of configuration changes using a combination of automated and human-driven mechanisms. This comprehensive approach results in an integrated solution that adeptly prioritizes the correction of misconfigured services based on their possible influence on the overall performance of the system. Acknowledgment The research activities are divided into three stages. The first phase is a thorough Literature Review to obtain insights and knowledge from current sources. This informs the succeeding System Design and Implementation phase, in which a prototype of the desired system is created. This prototype is subjected to a thorough review that considers issues such as accuracy and scalability. The prototype is exposed to real-world testing situations in the last phase, Evaluation and Validation, to fine-tune its functionality and improve its performance. The consequences of this research are considerable, with the potential to greatly improve the reliability of Windows Server settings. This research offers itself as a disruptive method with far-reaching advantages for organizations by reducing downtime, improving performance, and implementing cost-effective strategies.
Maintenance system, Automation, Self-healing, Predictive maintenance, Windows servers, Configuration Management, Fault Management, Error resolution, Machine learning, reliability, uptime, accuracy, efficiency, Web-based dashboard
Ruchiranga G.K.N., Bandara G.K.A.H., Rathnayake L.A.N.M., Ganepola G.A.T.S., Anjalie Gamage, Amali Gunasinghe, “Automated Self-Healing Maintenance System for Windows Server” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 10, pp 282-289, October 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.710036
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