Maintaince predictive system for data centres
Our idea focuses on optimizing IT infrastructure and data center management by predicting maintenance needs. The project uses metrics like CPU load, storage utilization, and temperature to assess risk levels and determine when maintenance is required. By analyzing these metrics, the system predicts the next service date, ensuring high availability of critical systems, reducing downtime, and preventing server crashes. The interactive tool, built using Python and Gradio, provides a user-friendly interface for IT managers to make informed decisions and streamline operations. Our AI-powered tool predicts maintenance needs based on key metrics. This prevents downtime, improves performance, and saves costs by enabling proactive action.
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