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Agentic AI System for Intelligent OS Patch Management

T. Madhu, R. Pushpakumari

Abstract


Operating system patch management plays a vital role in keeping computers secure, stable, and up to date. However, most existing update systems still rely on users to start or approve patches, which often causes delays and increases the risk of system vulnerabilities. To solve this issue, this project introduces an Agentic AI System for Intelligent OS Patch Management that works automatically without requiring user permission. The system continuously monitors key system parameters such as CPU load, memory usage, battery level, uptime, and C-drive storage space. Based on these real-time readings, a rule-based AI model decides whether it is the right time to install updates or if they should be postponed. The entire process is displayed on a Streamlit dashboard, which provides a clear view of system health, patch decisions, and update history. This AI-driven approach reduces human involvement, saves time, and improves patch reliability by ensuring updates occur only when the system is in a stable condition. Overall, the proposed system provides a smart, fully automated, and efficient solution for operating system maintenance.


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References


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