Runtime Log Compression for Memory-Constrained System Operations
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Solution Overview
Problem
Computing systems face memory constraints due to log file compilation during operations, leading to potential 'out of memory' errors and increased costs from using volatile RAM, which is expensive and limited in capacity.
Innovation Solution
Implementing a compression manager that analyzes and compresses system logs in real-time during execution, identifying and discarding non-targeted data to free up memory resources, allowing for continuous operation without the need for additional volatile memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If log files are compiled in volatile memory during operation execution, then log data is readily accessible for analysis, but memory capacity is consumed leading to potential 'out of memory' errors
Solution Approach 1:
The patent applies parameter changes by transforming the state of log data from uncompressed to compressed format, thereby changing the density and storage requirements. The compression manager dynamically adjusts compression parameters and thresholds to optimize memory usage while maintaining log accessibility, resolving the contradiction between reliable log storage and limited memory capacity
Solution Approach 2:
The patent extracts only the essential and relevant log data for retention while discarding redundant or less critical information. The compression manager identifies and extracts key log entries that must be preserved in volatile memory, separating them from data that can be compressed or moved to secondary storage, thus reducing overall memory consumption while maintaining system reliability
2Reliability
If volatile RAM capacity is increased to prevent 'out of memory' errors, then system stability is improved, but costs increase due to expensive volatile memory
Solution Approach 1:
The patent changes the storage parameter of log data by implementing compression algorithms that reduce the space requirements in volatile memory. By adjusting compression ratios and thresholds dynamically, the system maintains stability with reduced memory capacity, avoiding the need to increase expensive RAM resources
Solution Approach 2:
The patent creates compressed representations or summaries of log data that occupy less memory space while preserving essential information. Instead of storing complete uncompressed logs in volatile memory, the system maintains compressed copies or extracted key features, reducing memory requirements and associated costs while maintaining system reliability
3Quantity of substance
If log compression is implemented during operation execution, then memory usage is reduced, but computational resources are consumed by compression operations
Solution Approach 1:
The patent applies preliminary action by pre-defining compression thresholds, retention policies, and data prioritization rules before log compression begins. The compression manager is pre-configured with parameters for what constitutes critical log data versus compressible data, reducing the computational complexity during actual compression operations by avoiding real-time decision-making
Solution Approach 2:
The patent segments log data into different categories (critical, important, routine) and applies different compression strategies to each segment. This segmentation allows the system to focus computational resources on less critical data that can be compressed, while preserving critical data with minimal processing, thereby reducing overall computational complexity
Data Source
AI summary
Systems, apparatuses, and methods related log compression are described. In an example, a system log that identifies targeted data may be compiled in a memory resource during an execution of an operation using that memory resource. The system log may be analyzed utilizing a portion of the memory resource that would otherwise be available to be utilized in the execution of the operation. The system log may be compressed during the execution of the operation, the level or timing of such compression may be based on the analysis that occurs contemporaneous to or as a result of executing the operation. In some examples, compressing the system log may include discarding a portion of the system log. Compressing the system log may also include extracting the targeted data from the system log as the system log is being compiled and converting the extracted targeted data to structured data.