Central Diagnosis Server for Storage System Anomaly Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional technical support procedures for diagnosing issues in data storage systems are slow and unreliable, relying on manual data collection and comparison.
Innovation Solution
A central diagnosis server collects and stores previous state data from various data storage systems, allowing for automated comparison with current state data to identify anomalous behavior and diagnose root causes efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data collection and comparison is used, then technical support personnel can diagnose component issues, but the diagnosis process is slow and unreliable
Solution Approach 1:
The patent replaces manual mechanical processes (technicians physically collecting data, comparing documentation, and diagnosing issues) with an automated electronic system that collects component data, compares it against historical data and thresholds, and generates diagnoses automatically. This substitution eliminates human error and dramatically reduces diagnosis time while improving reliability.
Solution Approach 2:
The system enables components and storage systems to self-diagnose by automatically collecting their own operational data, comparing it against predefined thresholds and historical patterns, and generating diagnostic reports without requiring external technician intervention. This self-service capability provides immediate, consistent diagnoses.
2Productivity
If automated data collection and comparison is implemented, then diagnosis speed and reliability improve, but system complexity increases
Solution Approach 1:
The patent creates a universal diagnostic platform that can analyze multiple types of storage components (disks, storage processors, controllers) using the same automated data collection and comparison infrastructure. This multi-functional system handles diverse component types through standardized interfaces and configurable parameters, managing complexity through generalization rather than requiring separate systems for each component type.
Solution Approach 2:
The system introduces a centralized diagnostic server as an intermediary between storage components and technicians. This mediator automatically collects data from components, performs complex comparisons against historical data and thresholds, and presents simplified diagnostic results. The intermediary absorbs the computational complexity, leaving technicians with straightforward interpretation tasks.
Data Source
AI summary
An improved technique involves mapping differences between current data collected from a component and previous data collected from the component to anomalous behavior of the component. A central diagnosis server collects previous state data such as disk or CPU utilization from components of various data storage systems it supports. The server may store this data, indexed by identifiers such as events linked to the state data, in a central database for later reference. The server then compares current state data being received from a particular data storage system to previous state data stored in the database. In some arrangements, the server selects previous state data based on matching event identifiers corresponding to the current state data and previous state data. The central diagnosis server then determines anomalous behavior based on the difference between current and previous state data.