Web Container Internal Server Error Analysis
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Solution Overview
Problem
Current server error logs lack detailed information about internal server errors, making it difficult for administrators to identify and fix issues quickly, as they do not provide the root cause, message identifier, correlation identifier, or a compatible format, leading to inefficient problem-solving in complex web server environments.
Innovation Solution
Implementing monitoring utilities that include an internal server error counter and categorization entries within the web container to track occurrences and generate error reports with specific error categorization, source, and possible solutions, facilitating efficient identification and correction of errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the web server generates a generic error message for internal server errors, then the error handling is simple and quick to implement, but the error log lacks detailed information making it difficult for administrators to identify and fix issues
Solution Approach 1:
The patent segments error information into multiple categorical dimensions including error type, severity level, component source, and temporal patterns. This segmentation allows comprehensive error information to be organized in structured categories rather than a single undifferentiated log entry, resolving the contradiction by providing detailed information while maintaining systematic organization.
Solution Approach 2:
The patent adds multiple dimensions to error logging beyond simple occurrence recording. Error messages are enhanced with dimensional attributes such as categorization tags, frequency metrics, severity levels, and correlation identifiers. This dimensional expansion provides comprehensive error information without creating a monolithic complex system, as each dimension can be independently analyzed and filtered.
2Productivity
If administrators search the entire internal error log to identify web server problems, then no additional monitoring infrastructure is needed, but the time and effort required to identify and address errors increases significantly
Solution Approach 1:
The patent implements preliminary categorization and indexing of error logs with metadata tags before administrators need to search. Error occurrences are pre-processed with categorization entries that group similar errors, add temporal context, and assign priority levels. This preliminary organization enables administrators to quickly filter and identify relevant errors without manually searching through entire logs, thus improving productivity while reducing time loss.
Solution Approach 2:
The patent establishes feedback mechanisms where error patterns are continuously monitored and analyzed. The system provides feedback to administrators through aggregated error reports, trend analysis, and anomaly detection. This feedback loop enables rapid identification of recurring issues and their resolution progress, significantly improving error identification efficiency while reducing the time administrators spend on manual analysis.
3Loss of information
If the web server generates detailed error logs with comprehensive information, then administrators have all the data needed to diagnose problems, but the complexity of analyzing and processing this detailed information increases
Solution Approach 1:
The patent applies local quality by providing different levels of error information detail tailored to specific diagnostic needs. Rather than uniformly detailed logging for all errors, the system categorizes errors and provides enhanced detail only where necessary for specific error types or severity levels. This selective detail approach ensures comprehensive diagnostic information is available when needed while reducing overall analysis complexity through targeted information provision.
Solution Approach 2:
The patent transforms error log data by changing parameters such as aggregation time windows, categorization granularity, and filtering criteria. The system can dynamically adjust these parameters to balance information completeness with analysis simplicity. For example, errors can be aggregated by time periods or grouped by similarity metrics, transforming raw detailed logs into more manageable analyzed forms while preserving essential diagnostic information.
4Reliability
If monitoring utilities track every internal server error occurrence with counters and categorization, then error statistics and patterns can be identified, but the resource consumption and system overhead increase
Solution Approach 1:
The patent implements partial monitoring by focusing tracking resources on error types and patterns that are most significant for system reliability. Rather than equally monitoring every possible error occurrence, the system prioritizes tracking based on error severity, frequency thresholds, and business impact. This partial action approach maintains high monitoring accuracy for critical errors while reducing overall computational resource consumption by not exhaustively tracking every minor error event.
Data Source
AI summary
The present disclosure involves systems, software, and computer implemented methods for internal server error analysis. One process includes operations for identifying an internal server error associated with a particular type of error and returned by a web container. A counter of the number of internal server errors returned by the web container is incremented. The internal server error is also associated with an internal categorization of the particular type of internal server error, and the occurrence of the internal server error is added to a categorization entry generated based on the internal categorization of the error.