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Informative Article | Engineering Science | India | Volume 13 Issue 8, August 2024 | Rating: 3.7 / 10
AI-Powered Observability: A Journey from Reactive to Proactive, Predictive, and Automated
Ramakrishna Manchana
Abstract: The escalating complexity and scale of modern IT environments, coupled with the decentralization of IT infrastructure, necessitate a paradigm shift from traditional, reactive IT operations management to a proactive, intelligent, and automated approach. The integration of Artificial Intelligence (AI) into IT operations, often referred to as AIOps, has emerged as a transformative solution, offering the potential to revolutionize IT operations management by leveraging AI and machine learning's capabilities in data analysis, pattern recognition, and automation. The evolution from reactive incident response to predictive analytics and ultimately, automated closed-loop systems, underscores the transformative potential of AI in optimizing IT operations. The journey towards AI-powered IT operations necessitates a strategic roadmap that encompasses the gradual integration of AI capabilities, starting with establishing robust observability practices and progressing towards proactive, predictive, and ultimately, automated remediation. The overarching message is clear: AIOps represents a paradigm shift in IT operations management, empowering organizations to achieve operational efficiency, reduced downtime, enhanced security, and cost savings through the intelligent application of AI and machine learning.
Keywords: AIOps, IT Operations, Artificial Intelligence, Machine Learning, Observability, Proactive IT Operations, Predictive Analytics, Automated Closed-Loop Systems, Incident Response, Root Cause Analysis, Anomaly Detection, Capacity Planning, Self-Healing Systems, IT Infrastructure, Cloud Computing, Microservices, Edge Computing, Data Analysis, Automation
Edition: Volume 13 Issue 8, August 2024
Pages: 1745 - 1755