Title: AIOps research innovations, performance impact and challenges faced

Authors: Ajay Reddy Yeruva; Vivek Basavegowda Ramu

Addresses: Pleasanton, California – 94588, USA ' Hartford, Connecticut – 06103, USA

Abstract: Artificial intelligence for IT operations (AIOps) has become a vital element of the IT business, especially for software development in this Big Data and Internet of Things (IoT) era. AIOps is a robust solution that helps program managers and developers construct, execute, and boost online programs utilising AI and ML techniques. Productivity, security, performance, and ease of operation are sought-after benefits. Future operations may use AIOps, although the Methodologies section offers few techniques. This essay discusses AIOps development. This study highlights the deficiencies in research studies in several domains of AIOps and more so with cases anomaly detection, how to improve system performance leveraging AIOps, and root-cause-analysis (RCA) in the literature review section, along with suitable suggestions in the form of well-acclaimed performing techniques (Telesto, SLMAD, and language learning models) to ensure that this study covers difficulties and strategies to develop AIOPs solutions to establish a valid AIOps benchmark.

Keywords: AIOps; artificial intelligence for IT operations; performance; performance testing; analytics; DevOps; software cloud computing; IT& operations; Telesto; SLMAD and language learning models.

DOI: 10.1504/IJSSE.2023.133013

International Journal of System of Systems Engineering, 2023 Vol.13 No.3, pp.229 - 247

Received: 28 Aug 2022
Accepted: 10 Oct 2022
Published online: 24 Aug 2023 *

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