Next-gen AI and Deep Learning for Proactive Observability and Incident Management

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Published: Apr 6, 2022
DOI: https://doi.org/10.61841/turcomat.v13i03.14765
Keywords:
Preventive Checking, Management of Occurrences, Artificial Intelligence, Artificial Brain, Strategic Fixing, Identification of Outliers, Actionable Notifications, I&T Generations, Report on Modeling, Real-World Scenarios

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Sai Krishna Manohar Cheemakurthi
Independent Researcher
Naresh Babu Kilaru
Independent Researcher
Vinodh Gunnam
Independent Researcher

Abstract

I need to stress that maintaining continuous IT infrastructure and application availability is critical in today's fast-growing digital world. Conventional observability and incident handling tools are outdated, slow, and mostly manual, which cannot effectively address the new and challenging world. Therefore, this paper examines how next-generation artificial intelligence and deep learning methods can be applied to improve the ability to observe and manage incidents before they occur. Utilizing the all-encompassing simulation reports, the real-time scenario analysis, and the graphical representations, we prove the applicability and functionality of those innovative technologies with the power of anticipating, detecting, and remedying those events before they affect the end-users. In addition, we discuss the issues related to data, models, and systems for these technologies and explain the proper ways to cope with them. Consequently, the research points out how using AI and deep learning enhances the effectiveness and efficiency of handling incidents, leading to more robust IT environments.

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How to Cite
Cheemakurthi, S. K. M., Kilaru, N. B., & Gunnam, V. . (2022). Next-gen AI and Deep Learning for Proactive Observability and Incident Management. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 13(03), 1550–1564. https://doi.org/10.61841/turcomat.v13i03.14765
Issue
Vol. 13 No. 03 (2022)
Section
Research Articles
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