Abstract
This technology described herein relates to automated, intelligent analysis of log data from complex software systems. The technology employs a two-tiered Large Language Model (LLM) architecture to detect anomalies and generate context-rich incident reports. The first tier LLM performs a rapid, broad analysis of all incoming log streams to flag potential issues. Flagged events are escalated to a second tier LLM with a long context window, which performs deep, multi-modal analysis by correlating log strings across services with time-series data and deployment events. The output is a high-confidence alert and a human-readable summary that explains the anomaly, its likely impact, and probable root causes. The system enables faster, more effective incident responses.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
N/A, "Automated Log Analysis and Incident Response", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/8534