Adaptive Trace Logging Module for Software Performance
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Solution Overview
Problem
Current trace logging techniques either consume excessive computing resources, leading to performance degradation or fail to capture important diagnostic messages due to limited administrator-specified severity levels, making it difficult to troubleshoot software issues efficiently.
Innovation Solution
An adaptive trace logging module that dynamically adjusts trace logging levels based on input data about trace logging behavior and computing resources, such as disk space and CPU usage, and automatically changes the logging level in response to detected abnormal conditions, temporarily increasing logging to capture relevant messages during issues and reducing resource consumption when stable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the trace logging level is set to a relatively low severity such as Info, then more trace logging messages are captured in the trace log, but excessive computing resources are consumed leading to performance degradation
Solution Approach 1:
The trace logging level is made dynamic rather than static. The system automatically adjusts the logging level based on runtime conditions, transitioning between different severity thresholds as needed. This allows the system to capture detailed logs when problems occur while maintaining performance during normal operation.
Solution Approach 2:
The severity threshold parameter of the trace logging level is changed dynamically based on system state. When an abnormal condition is detected, the system lowers the severity threshold to capture more detailed messages; when stable, it raises the threshold to reduce resource consumption.
2Productivity
If the trace logging level is set to a relatively high severity such as Warning, then computing performance is maintained, but important diagnostic messages are missed
Solution Approach 1:
The system dynamically switches between high and low logging levels based on operational context. During normal stable operation, a high logging level maintains performance; when abnormal conditions are detected, it transitions to a low logging level to capture diagnostic messages.
Solution Approach 2:
The system monitors system state and uses this feedback to automatically adjust the logging level. When problems or abnormal conditions are detected through monitoring, the system responds by lowering the logging level to ensure diagnostic messages are captured.
3Ease of operation
If a fixed administrator-specified trace logging level is used, then configuration is simple, but the system cannot adapt to varying operational conditions
Solution Approach 1:
The trace logging system serves itself by automatically adjusting its own logging level based on monitored system conditions. No administrator intervention is needed - the system autonomously determines when to increase or decrease logging detail based on its own operational state.
Solution Approach 2:
The logging level transitions from a static administrator-specified value to a dynamic system-determined value that automatically adapts to operational conditions while maintaining ease of initial configuration.
Data Source
AI summary
Techniques for adaptive trace logging include, in one embodiment, obtaining input data on trace logging behavior and computing resources used by trace logging. Based on the obtained input data, an adaptive trace logging module automatically takes action at runtime to reduce the amount of computing resources consumed by tracing logging. For example, the action taken may include decreasing a trace logging level of an executing software program to reduce the number of trace logging messages added to a trace log. In another embodiment, the techniques include detecting a condition of an executing software program that warrants a change to a trace logging level of the executing program. The adaptive trace logging module automatically changes the trace logging level of the executing program as-needed for the detected condition. For example, the adaptive trace logging module may increase the trace logging level of an executing program upon detecting a deadlock or other abnormal condition of the executing program. By automatically increasing the trace logging level upon detecting an abnormal condition, additional trace logging messages may be written to a trace log aiding diagnosis and troubleshooting of the condition.