Leveraging LLMs for Structured Information Extraction and Analysis from Cloud Incident Reports (Work In Progress Paper)

Abstract

Incident management is essential to maintain the reliability and availability of cloud computing services. Cloud vendors typically disclose incident reports to the public, summarizing the failures and recovery process to help minimize their impact. However, such reports are often lengthy and unstructured, making them difficult to understand, analyze, and use for long-term dependability improvements. The emergence of LLMs offers new opportunities to address this challenge, but how to achieve this is currently understudied. In this paper, we explore the use of cutting-edge LLMs to extract key information from unstructured cloud incident reports. Our study provides tools, methodologies, and insights for leveraging LLMs to accurately and efficiently extract incident-report information. The FAIR data and code are publicly available at: https//github.com/atlarge-research/llm-cloud-incident-extraction