Storage Array Problem Signature Detection and Corrective Deployment
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Solution Overview
Problem
Managing disparate problems across multiple storage arrays in data centers is challenging due to their varying types and susceptibility to different issues, and existing corrective measures often impact storage array performance.
Innovation Solution
A system that proactively detects problems in storage arrays by analyzing event data for a 'problem signature' and automatically deploys corrective measures without user intervention to prevent violations of operational policies, using a cloud-based storage array services provider.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If corrective measures are deployed manually with user intervention, then user control and approval are maintained, but response time increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by pre-defining corrective measures and policies before problems occur. When a problem is detected, the system automatically executes the pre-planned corrective measures without waiting for user approval, thereby reducing response time while maintaining reliability through predefined control logic.
Solution Approach 2:
The storage array system performs self-service by automatically detecting problems, evaluating policies, and deploying corrective measures without requiring continuous user intervention. The system monitors itself, makes decisions based on operational policies, and executes corrections autonomously, improving productivity while maintaining controlled reliability.
2Productivity
If corrective measures are deployed automatically without user intervention, then response time decreases and productivity increases, but user control and approval are reduced
Solution Approach 1:
The system implements feedback mechanisms where operational data from storage arrays is continuously monitored and fed back to the management system. This feedback enables automatic detection of problems and triggers appropriate corrective measures, maintaining user control through transparent monitoring while achieving fast automated responses.
Solution Approach 2:
The system changes operational parameters by automatically adjusting storage array settings based on detected problems and operational policies. Instead of manual parameter modification, the system dynamically modifies parameters such as performance thresholds, operational modes, or configuration settings to resolve issues automatically, improving response time while keeping user control through policy-based automation.
3Reliability
If storage arrays are managed individually with customized corrective measures, then specific problem resolution is optimized, but device complexity increases and difficulty of detecting and measuring problems increases
Solution Approach 1:
The system achieves universality by creating a unified management platform that handles diverse storage array types through common problem detection and corrective measure deployment mechanisms. Instead of individualized management for each storage array type, the system uses universal policies and automated responses that work across multiple array configurations, reducing management complexity while maintaining effective problem resolution.
Solution Approach 2:
The system applies segmentation by dividing storage array management into modular components: problem detection modules, policy evaluation modules, and corrective measure deployment modules. This segmentation allows complex problems to be broken down into manageable detection and response units, reducing overall management complexity while maintaining effective targeted resolution through modular functionality.
4Reliability
If proactive corrective measures are deployed based on problem signatures, then early detection and prevention are achieved, but measurement precision requirements increase
Solution Approach 1:
The system performs preliminary action by pre-identifying problem signatures and patterns before actual failures occur. By monitoring for precursor events and detecting patterns that indicate emerging problems, the system enables early detection and preventive corrective measures. This preliminary detection approach improves reliability by addressing issues before they manifest as failures, while managing measurement precision through predefined pattern recognition rather than requiring ultra-precise real-time measurements.
Data Source
AI summary
A method may include detecting, by a computing device based on a problem signature, that a system has experienced a problem that is associated with the problem signature, wherein the problem signature comprises a specification of a pattern of events indicative of the particular problem experienced by at least one other system; determining that the particular problem violates an operational policy of the system; and deploying, without user intervention, one or more corrective measures that modify the system to resolve the problem.