Runtime Error Manager for Automated System Fault Resolution
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Solution Overview
Problem
In complex computer systems, runtime errors often go undetected or are not timely reported due to the complexity of error detection and manual procedures, leading to increased maintenance resources being spent on fixing propagated errors.
Innovation Solution
Implementing a runtime error manager across the computer system landscape to automatically generate and filter error dumps, supplement relevant data, and notify responsible users for swift error resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual error detection and reporting procedures are used, then system complexity is reduced, but error detection speed and timeliness deteriorate
Solution Approach 1:
The system enables self-service error detection and reporting by automatically generating error dumps, filtering relevant data portions, and notifying responsible users without manual intervention. The runtime error manager autonomously monitors system nodes, collects error information, and initiates notification procedures, allowing the system to detect and report errors independently rather than relying on manual detection processes
Solution Approach 2:
The runtime error manager acts as an intermediary component between system errors and users. It intercepts error dumps generated across system nodes, processes them by filtering relevant data portions, supplements information, and forwards notifications to appropriate users. This intermediary mechanism bridges the gap between raw error generation and user awareness, enabling timely error detection while maintaining manageable system complexity through a dedicated intermediary component
2Reliability
If comprehensive error monitoring is implemented across all system nodes, then error detection capability is improved, but system resource consumption increases
Solution Approach 1:
The system extracts only the relevant data portions from comprehensive error dumps generated across system nodes. The runtime error manager filters out unnecessary information and retains only critical error details needed for diagnosis and resolution. This extraction approach enables thorough error monitoring across all nodes while consuming minimal system resources by processing only essential information rather than entire error dumps
Solution Approach 2:
The system implements partial action by selectively monitoring and processing error information from system nodes. Instead of analyzing every detail of each error dump, the runtime error manager applies filtering rules to process only relevant data portions. This partial processing approach provides sufficient error detection capability across the distributed system while significantly reducing the computational resources required compared to comprehensive analysis of all error data
3Loss of information
If error dumps are filtered to retain only relevant data portions, then information quality for error resolution is improved, but data processing time increases
Solution Approach 1:
The runtime error manager applies filtering rules in advance to error dumps before they are fully processed or stored. By pre-filtering data portions as error dumps are generated across system nodes, the system prepares refined error information ready for immediate use. This preliminary filtering action ensures high-quality error information is available when needed while minimizing additional processing time during actual error resolution activities
Data Source
AI summary
Systems and methods for advanced management of runtime errors are described herein. Based on a preference, a runtime error manager selects one or more error dumps generated in a computer system landscape. The runtime error manager filters one or more data portions from the selected error dumps. The filtered data portions are supplemented with additional information collected from the nodes of the computer system landscape, or received from external systems. The data portions and the supplemental data are used to assign users responsible to resolve one or more of the logged runtime errors. The data portions and the supplemental information are used to create and send notifications to the responsible users or to instantiate and manage workflows in behalf to the responsible users.