International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 07 | July 2024
p-ISSN: 2395-0072
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The Impact of Artificial Intelligence on Enterprise Monitoring: Transforming Applications, Infrastructure and Networks Jayaram Nori Broadcom Inc, USA ------------------------------------------------------------------------***-------------------------------------------------------------------------
Abstract The rapid advancement of artificial intelligence (AI) is revolutionizing enterprise monitoring, enabling organizations to proactively manage and optimize their increasingly complex and distributed IT environments. This article explores the profound impact of AI on monitoring applications, infrastructure, and networks, highlighting the key AI technologies driving this transformation, such as machine learning, deep learning, natural language processing, and computer vision. By leveraging these technologies, enterprises can achieve unparalleled visibility, automate anomaly detection, enable predictive maintenance, and drive operational efficiencies across their IT ecosystems. The article delves into the specific applications of AI in monitoring, including intelligent traffic analysis, root cause analysis, capacity planning, and energy optimization. It also discusses the significant benefits of AI-powered monitoring, such as faster issue detection and resolution, reduced manual effort, and improved scalability. However, the article also acknowledges the challenges and considerations associated with implementing AI in enterprise monitoring, such as the need for high-quality data, the potential for algorithmic bias, and the skills gap in AI among IT teams. Looking ahead, the article explores future directions in AI-driven monitoring, including the emergence of advanced AIOps platforms, the adoption of explainable AI, the rise of edge AI for distributed monitoring, and the integration of digital twin technology. Ultimately, this article provides a comprehensive overview of how AI is reshaping enterprise monitoring and empowering organizations to build resilient, efficient, and self-optimizing IT environments in the era of digital transformation. Keywords: Artificial Intelligence (AI), Enterprise Monitoring, AIOps (Artificial Intelligence for IT Operations), Predictive Maintenance, Anomaly Detection
1. Introduction In recent years, enterprise IT environments have become increasingly complex, distributed, and dynamic. The widespread adoption of cloud services, microservices architectures, containerization, and Internet of Things (IoT) devices has resulted in highly intricate technology ecosystems that pose significant challenges for traditional monitoring approaches [1]. As
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