Dynamic Log Pattern Adaptation for Storage and Integrity Trade-offs
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Solution Overview
Problem
In data center management systems, especially for Platform as a Service (PaaS), it is challenging to manage log deletion effectively due to changes in device operation procedures, leading to inappropriate deletion of log items that may be needed for analysis, as existing methods rely on pre-defined regularities that become obsolete with procedure changes.
Innovation Solution
A log management system that suspends log item deletion when a change in operation procedures is detected, updates log pattern identification information, and uses the new patterns to determine suitable deletion criteria, ensuring that critical logs for analysis are not deleted prematurely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If log items are deleted according to pre-defined regularity patterns, then storage space is saved and hardware resource usage is reduced, but log data needed for analysis may be deleted when operation procedures change
Solution Approach 1:
The log deletion system dynamically adapts to changes in device operation procedures by continuously monitoring operation information and updating log patterns. When a procedure change is detected, the system automatically adjusts which log items should be deleted, ensuring that dynamically generated log patterns replace static pre-defined patterns. This resolves the contradiction by making the deletion criteria flexible and responsive to actual operational changes while maintaining storage efficiency.
Solution Approach 2:
The system implements feedback mechanisms by analyzing operation information from devices and comparing it against known operation procedures. When discrepancies indicating procedure changes are detected, the system feeds this information back to update the log pattern identification, ensuring future deletions align with current operational realities. This feedback loop prevents premature deletion of critical logs while maintaining storage optimization.
2Extent of automation
If pre-defined regularity patterns are used for log deletion, then log management is automated and efficient, but the system cannot adapt when device operation procedures change
Solution Approach 1:
The system transitions from static pre-defined patterns to dynamic procedure-adaptive patterns by continuously monitoring device operation information. The log deletion automation remains high-level but becomes adaptive through automatic detection of procedure changes and dynamic generation of appropriate log patterns. This maintains automation efficiency while gaining adaptability to operational changes.
Solution Approach 2:
The system performs self-updating by automatically detecting changes in device operation procedures and generating new log patterns without manual intervention. The log management system serves itself by autonomously adapting its deletion criteria based on monitored operation information, combining automation with adaptability through self-service capability.
3Reliability
If all log items are retained for analysis, then data integrity is maintained, but hardware resource usage increases
Solution Approach 1:
The system applies different retention qualities to different log items based on their relevance to current operation procedures. Critical logs that may be needed for analysis are retained with high quality, while redundant logs following established patterns are deleted to save storage resources. This local differentiation of retention quality maintains data integrity for important logs while optimizing hardware resource usage through selective deletion.
Solution Approach 2:
The system dynamically changes the retention parameter for log items based on detected procedure changes. When operations change, the system adjusts which log patterns should be retained versus deleted, optimizing the balance between data integrity and resource usage. This parameter adaptation ensures that storage resources are allocated efficiently while maintaining necessary log data for analysis.
Data Source
AI summary
A non-transitory computer-readable recoding medium having stored therein a log management program that causes a computer to execute a process that includes suspending, in accordance with a change in information related to an operation of a device under management, deletion of log items of log data of the device performed in accordance with log pattern identification information generated according to a regularity of the log items of the log data, determining, according to a change situation of the information related to the operation, suitability of the deletion of the log items performed in accordance with the log pattern identification information, and updating, when the deletion is determined to be unsuitable, the log pattern identification information according to a log item stored after the deletion has been suspended.