Transaction Log Evaluation Module for Proactive Monitoring
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Solution Overview
Problem
Existing transaction monitoring systems generate raw data logs that are not easily accessible or understandable, limiting their utilization for proactive maintenance of computing systems, and thus fail to leverage the full potential of transaction log information for monitoring and maintaining computing system health.
Innovation Solution
A computer-implemented method and system that parse and evaluate transaction log information to automatically identify deviations in transaction metrics, generate alerts for potential issues, and dynamically adjust thresholds to prevent false alerts, enabling real-time monitoring and proactive management of computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If transaction monitoring agents store transaction information in raw data format, then data storage is simple and direct, but the transaction information is not easily accessible and not readily understandable to end users
Solution Approach 1:
The patent introduces a transaction log evaluation module as an intermediary between the raw transaction logs and the end users. This module parses the raw transaction log information, evaluates transaction metrics (such as transaction rate and latency), and presents the data in a user-friendly format. The intermediary transforms the unprocessable raw data into actionable insights without requiring users to directly handle the complex raw log formats.
Solution Approach 2:
The patent changes the parameters of transaction log information from raw, unprocessed format to processed metrics including transaction rate, latency averages, and other evaluated parameters. By transforming the data representation from raw logs to structured metrics with specific units and formats, the system makes the information both accessible and understandable to end users while maintaining the underlying data integrity.
2Measurement precision
If transaction logs are only utilized during investigation of technical issues, then the logs provide detailed information for post-event analysis, but the enterprise does not take full advantage of the information for proactive maintenance
Solution Approach 1:
The patent implements preliminary action by continuously evaluating transaction metrics from logs and generating alerts before actual technical issues occur. The system monitors transaction rate and latency trends in real-time, detecting deviations from normal patterns that indicate potential problems. This allows the enterprise to take proactive maintenance actions before failures happen, transforming the utility of logs from post-event investigation to pre-event prevention.
Solution Approach 2:
The patent establishes a feedback loop where transaction log information is continuously evaluated, compared against thresholds and historical data, and used to generate real-time alerts. This feedback mechanism enables the system to adapt to changing conditions and provide timely notifications about potential issues, allowing the enterprise to respond proactively rather than reactively to technical problems.
3Reliability
If the system continuously monitors and compares transaction metrics, then real-time detection of issues is improved, but computational resources and processing time are consumed
Solution Approach 1:
The patent applies partial action by selectively evaluating only the most critical transaction metrics (such as transaction rate and latency) rather than processing every possible log detail. The system focuses computational resources on key parameters that most strongly indicate system health, using threshold-based filtering and historical comparison to minimize unnecessary processing while maintaining effective real-time monitoring.
Data Source
AI summary
Aspects of the present disclosure provide systems and methods directed toward monitoring transactions between computing resources of a computing system. A transaction agent may monitor transactions between computing resources and generate transaction log information corresponding to the transactions. A current transaction rate for a current time period and a previous transaction rate for a previous time period may be automatically obtained based on transaction log information. The current transaction rate may be compared to the previous transaction rate, and a transaction rate alert may be generated responsive to determining that the previous transaction rate exceeds the current transaction rate. A current and previous transaction latency average may also be obtained based on transaction time information of the transaction log information. The transaction latency averages may be compared, and a transaction latency alert may be generated responsive to determining that the current transaction latency average exceeds the previous transaction latency average.


