Adaptive Log Level Control for Dynamic System Monitoring
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Solution Overview
Problem
Conventional logging systems face challenges in dynamically adjusting log severity levels based on user interactions, often resulting in insufficient logging when issues arise, leading to inefficient troubleshooting and potential data loss or excessive resource usage.
Innovation Solution
An adaptive log level control system that monitors user interactions with a target application, identifies usage patterns indicative of problems, and adjusts log severity levels incrementally to provide optimal logging depth without compromising application performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If log severity levels are set to capture detailed information for troubleshooting, then diagnostic capability is improved, but system performance and resource usage deteriorate
Solution Approach 1:
The log severity level is transformed from a static configuration to a dynamic parameter that automatically adjusts based on detected usage patterns. The system monitors user interactions and application behavior in real-time, increasing log detail only when problematic patterns are identified, and reducing detail during normal operation to maintain system performance.
Solution Approach 2:
The system changes the log severity level parameter dynamically based on detected usage patterns. When patterns indicating potential problems are detected, the log level is adjusted to capture more detailed information. When normal operation is detected, the log level is reduced to minimize performance impact.
2Measurement precision
If log severity levels are increased to capture more detailed information, then troubleshooting effectiveness is improved, but resource usage and data volume worsen
Solution Approach 1:
Instead of uniformly increasing log detail across all operations, the system applies detailed logging locally only to specific operations or time periods where problems are detected. Normal operations continue with minimal logging, while problematic operations trigger increased logging detail only for those specific instances.
3Device complexity
If static log levels are used for all operations, then system simplicity is maintained, but adaptability to different operational states deteriorates
Solution Approach 1:
The logging system becomes self-regulating by automatically monitoring its own operational context and adjusting log levels without external intervention. The system detects usage patterns and autonomously determines when to increase or decrease logging detail, eliminating the need for manual configuration changes.
Solution Approach 2:
The system implements a feedback loop where user interactions and application behavior are continuously monitored, analyzed for problematic patterns, and used to adjust log severity levels. This closed-loop control enables the system to adapt to different operational states automatically.
Data Source
AI summary
Embodiments of systems and methods for adapting a log severity level that is applied to log files associated with a target application based on user interaction. In an illustrative, non-limiting embodiment, an adaptive log level control system includes computer-executable instructions for monitoring user interaction with a target application executed on the IHS, identifying a usage pattern of the user interaction, and determining that the usage pattern is indicative of a problem with the target application. The instructions may then adjust a log severity level of log files associated with the target application according to the detected problem.