Autonomic Failure Detection Using Cached Dependency Segments
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Solution Overview
Problem
Autonomic computing systems face challenges in accurately detecting root causes of failures due to complex dependency models, which can lead to reduced performance and usability, and may result in incorrect identification of failure causes due to the lack of system configuration information in dependency models.
Innovation Solution
An apparatus and method that collect system history information, generate detection rules, and add partial configuration information to symptoms to improve failure event detection accuracy by considering system configuration, thereby enhancing the identification of root cause events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the dependency model is scanned from upstream to downstream to identify root cause, then detection accuracy is improved, but scanning time increases significantly and performance deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-scanning and storing dependency model information in a cache memory before actual failure detection occurs. The dependency relationships are analyzed and prepared in advance, so when a failure event happens, the system can quickly retrieve pre-computed dependency paths without performing time-consuming scans at the moment of detection, thus resolving the contradiction between comprehensive scanning for accuracy and time consumption.
2Measurement precision
If the dependency model is scanned everywhere to ensure complete root cause identification, then detection accuracy is improved, but system complexity and processing overhead increase
Solution Approach 1:
The patent segments the dependency model into manageable units and stores them in a cache structure with organized dependency relationships. Instead of scanning the entire dependency model at once, the system divides it into cached segments that can be selectively accessed based on the failure event, reducing processing complexity while maintaining detection accuracy through targeted retrieval of relevant segments.
3Quantity of substance
If dependency information is stored without system configuration information, then storage efficiency is improved, but root cause identification accuracy decreases due to inability to verify component relationships
Solution Approach 1:
The patent merges dependency model information with system configuration information by integrating configuration data directly into the cached dependency structure. This combination allows the system to store component relationships, configuration details, and dependency paths together in a unified cache, enabling accurate root cause identification through verification of both dependency relationships and configuration states without significantly increasing storage overhead.
Data Source
AI summary
In a mechanism for supporting detection of a failure event, history information of a system including log information of the system including plural components and/or failure information output from each component upon occurrence of a failure in the system is collected. A detection rule for detecting an event included in a component related to the failure that has occurred is generated, and a symptom with additional information added to the generated detection rule is applied to detect the event that has caused the failure. System configuration information as configuration information of the system is acquired, and from the acquired system configuration information, partial configuration information as system configuration information related to the component that sent out the event the selection of which has been accepted is extracted. The extracted partial configuration information is added to the symptom to update the symptom.