Three-Tier Error Search for Faster Root Cause Resolution
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Solution Overview
Problem
Existing systems struggle to quickly identify and resolve errors in computer systems, particularly in networked environments and cloud computing, due to the complexity and variability of configurations, leading to increased downtime and costs.
Innovation Solution
A three-tiered mechanism for error identification and resolution, utilizing a local data store, a global data store of similarly configured systems, and a global data store of all systems, with a clustering mechanism to identify the most relevant cause and solution, prioritizing local issues and employing a K-nearest neighbor algorithm for similarity matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single global data store is used to search for error causes across all computer systems, then the coverage and comprehensiveness of error analysis is improved, but the search time and computational complexity increase significantly
Solution Approach 1:
The patent divides the global data store into multiple hierarchical levels: a local data store for the specific computer system, a regional data store for similarly configured systems, and a global data store for all systems. This segmentation allows the error analysis to start locally and expand outward only when necessary, significantly reducing search time while maintaining comprehensive coverage.
Solution Approach 2:
The patent introduces a hierarchical dimension to the data store structure, organizing error data across multiple levels of granularity. This dimensional approach enables the system to search through smaller, more relevant datasets first (local level) before expanding to larger datasets (global level), optimizing the trade-off between search speed and comprehensiveness.
2Measurement precision
If AI-based techniques are used to determine error causes, then the accuracy of root cause analysis is improved, but the dependency on training data and system complexity increases
Solution Approach 1:
The patent pre-processes and organizes error data from multiple sources into structured data stores before actual error analysis is needed. This preliminary organization of data reduces the complexity of AI-based analysis during actual error occurrence, as the system only needs to query pre-organized data rather than processing raw data in real-time.
Solution Approach 2:
The patent introduces data stores as intermediary structures between the error detection system and AI analysis algorithms. These data stores serve as mediators that pre-process and organize information, reducing the computational burden on AI algorithms and making the overall system more manageable and less complex.
3Reliability
If local data is prioritized in error analysis, then the relevance and applicability of solutions is improved, but the search scope is reduced
Solution Approach 1:
The patent segments the search process into sequential phases: first searching local data for high-relevance matches, then expanding to regional and global data stores if needed. This segmentation allows the system to prioritize local relevance while maintaining the ability to search broader scopes when necessary, resolving the contradiction between relevance and versatility.
Solution Approach 2:
The patent implements a dynamic search strategy where the search scope adapts based on initial results. If local data yields relevant solutions, the search remains localized; if not, the search automatically expands to regional and global levels. This dynamic adjustment allows the system to balance solution relevance with search scope flexibility.
Data Source
AI summary
An indication that indicates an occurrence of an error in a local computing system is received. A first-tier search comprising searching a local data store corresponding to the local computing system in an effort to determine a cause of the error is executed. In response to determining that the first-tier search is unable to determine the cause of the error, a second-tier search of a global data store is executed, wherein the second-tier search comprises searching for the error in one or more computer systems that are configured similarly to the local computing system. In response to determining that the second-tier search is unable to determine the cause of the error, a third-tier search of the global data store is executed, wherein the third-tier search comprises searching for the error in additional one or more computer systems that are not similarly configured to the local computing system.