Computer Management System for Early Detection of Failing Hardware
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Solution Overview
Problem
In large datacenter environments, identifying failing hardware components in computer systems before they cause significant performance degradation or failure is challenging due to the complexity of managing thousands of computers and the variability in performance metrics across devices.
Innovation Solution
A computer management system that tracks performance counters across multiple devices executing similar workloads, uses statistical analyses to identify outliers by comparing individual device deviations to the group mean, flagging devices with statistically significant deviations as potential problems, and continuously monitors various performance indicators to detect hardware or software issues early.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If performance counters are tracked across multiple devices to identify failing hardware, then detection precision is improved, but device complexity increases
Solution Approach 1:
The system segments the monitoring task by dividing it into multiple independent components: performance counter collection from individual devices, statistical analysis module that processes the collected data, and alert generation system. This segmentation allows each component to be optimized independently while maintaining overall system effectiveness in detecting failing hardware.
Solution Approach 2:
The patent introduces statistical analysis as an intermediary layer between raw performance counter data and failure detection. Instead of directly monitoring individual device metrics, the system uses statistical comparisons across multiple devices to identify anomalies, thereby improving detection precision while managing complexity through abstraction.
2Reliability
If statistical analysis is performed on performance counters to identify outliers, then reliability is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary statistical analysis by continuously collecting performance counters and establishing baseline statistics from multiple devices. This preliminary action enables the system to quickly identify outliers when they occur, improving reliability without significant time loss because the analytical framework is already in place and ready to detect anomalies.
Solution Approach 2:
The patent replaces manual or reactive hardware monitoring with automated statistical analysis systems. This substitution allows continuous monitoring and analysis to be performed efficiently without human intervention, reducing the time loss associated with manual inspection while maintaining high reliability through systematic outlier detection.
3Measurement precision
If multiple performance indicators are monitored across devices, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system implements a universal monitoring framework that can track multiple performance indicators (CPU usage, memory utilization, disk I/O, network traffic) across different device types using the same statistical analysis approach. This multi-functionality improves measurement precision by covering various aspects of device performance while managing complexity through a unified monitoring architecture.
Data Source
AI summary
A computer management system may track services on multiple computers executing the same workload. Various performance counters may be retrieved from the computers and analyzed to identify those with low deviations and low mean deviations. Statistical tests may then be used to compare the values of a particular computer to the deviation of the group of computers to identify outliers, which may indicate degraded performance and imminent failure of the computer. The management system may analyze any collectable performance related parameter to identify outlying systems.