Cloud Incident

Cloud incident management aims to automate the complex process of identifying and resolving issues in large-scale cloud services, reducing downtime and manual effort for engineers. Current research heavily utilizes large language models (LLMs), such as GPT-3 and GPT-4, employing techniques like in-context learning and prompt engineering to improve root cause analysis and mitigation recommendation accuracy. This work focuses on leveraging diverse data sources, including logs, monitoring data, and historical incident reports, to enhance the performance and reliability of AI-driven incident management systems, ultimately improving service reliability and operational efficiency.

Papers

February 15, 2024

X-lifecycle Learning for Cloud Incident Management using LLMs
Drishti Goel, Fiza Husain, Aditya Singh, Supriyo Ghosh, Anjaly Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
Medical LLM Context Aware Contextual Information Large Scale Cloud Incident Management Contextual Data Cloud Incident

January 24, 2024

Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
Xuchao Zhang, Supriyo Ghosh, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
Context Learning GPT 4 Root Cause Incident Management Cloud Incident

September 11, 2023

PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
GPT 4 Soft Augmentation Root Cause Calibrated Confidence Confidence Estimation Model LLM Confidence Cloud Incident

January 10, 2023

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan
Domain Knowledge Root Cause Production Incident Incident Management Adaptive Mitigation Cloud Incident

April 21, 2022

Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps
Amrita Saha, Steven C. H. Hoi
Downstream Task Root Cause AIOps Model Incident Report Cloud Incident

Cloud Incident

Papers

X-lifecycle Learning for Cloud Incident Management using LLMs

Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4

PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models

Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps