Configuration Fault Localization in Shared Cloud Resources
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Solution Overview
Problem
Conventional techniques for localizing configuration faults in distributed environments are limited by the reliance on resource dependency information and event correlation, which becomes increasingly complex in cloud computing due to the growth in system size and events, making it difficult to detect configuration faults effectively.
Innovation Solution
A method that involves receiving structural clusters for an environment, identifying configuration parameters and dependencies, building a configuration map, and ascertaining configuration fault occurrences using equivalence rules and differential configuration analysis to isolate faults in shared resources and configuration nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques relying on resource dependency information and event correlation are used, then fault localization can be performed, but the complexity increases considerably in shared resource environments due to system size growth
Solution Approach 1:
The patent segments the configuration management system into distinct modules: configuration parameter extraction module, dependency analysis module, fault localization module, and configuration map generation module. This segmentation allows each module to handle specific aspects of the complex system independently, reducing overall system complexity while maintaining fault localization capability in shared resource environments
Solution Approach 2:
The patent introduces a configuration map as an intermediary data structure that mediates between the complex shared resource environment and the fault localization process. The configuration map organizes configuration parameters, dependencies, and component relationships in a standardized format, simplifying the fault localization task despite the underlying system complexity
2Reliability
If conventional event correlation techniques are used, then fault detection can be performed, but granular event data availability is limited
Solution Approach 1:
The patent performs preliminary extraction and organization of configuration parameters and their dependencies before fault detection is needed. By pre-building the configuration map with all necessary parameter relationships and dependency information, the system eliminates the need for granular event data during actual fault detection, as the configuration map provides the necessary contextual information in advance
Solution Approach 2:
The patent creates a virtual copy of the configuration state through the configuration map, which replicates the essential relationships and dependencies without requiring access to actual granular event data. This virtual representation allows fault localization to proceed using synthesized configuration information rather than relying on limited event data
3Adaptability or versatility
If shared resource models are adopted in cloud computing, then resource utilization improves, but the complexity of fault localization increases due to increased system size and events
Solution Approach 1:
The patent designs a universal configuration map structure that can represent multiple types of shared resources (computing, storage, networking) and their various dependency relationships using a single standardized framework. This multi-functional approach allows the same fault localization mechanism to handle diverse shared resource scenarios without increasing complexity
Solution Approach 2:
The patent transforms the fault localization approach by changing from monitoring individual resource states to analyzing configuration parameter relationships. By shifting the focus to parameter dependencies and their changes within the configuration map, the system can handle the increased complexity of shared resource environments through parameter-based analysis rather than event-based analysis
Data Source
AI summary
Methods and arrangements for fault localization. Structural clusters for an environment are received, and configuration parameters and dependencies for components in the structural clusters are identified. A configuration map is built, and a configuration fault occurrence is ascertained.