Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

Ensuring the reliability and availability of cloud services necessitates efficient root cause analysis (RCA) for cloud incidents. Traditional RCA methods, which rely on manual investigations of data sources such as logs and traces, are often laborious, error-prone, and challenging for on-call engineers. In this paper, we introduce RCACopilot, an innovative on-call system empowered by the large language model for automating RCA of cloud incidents. RCACopilot matches incoming incidents to corresponding incident handlers based on their alert types, aggregates the critical runtime diagnostic information, predicts the incident's root cause category, and provides an explanatory narrative. We evaluate RCACopilot using a real-world dataset consisting of a year's worth of incidents from Microsoft. Our evaluation demonstrates that RCACopilot achieves RCA accuracy up to 0.766. Furthermore, the diagnostic information collection component of RCACopilot has been successfully in use at Microsoft for over four years

How does digital transformation drive innovation in Chinese agribusiness: Mechanism and micro evidence

This paper investigates the impact of digital transformation on innovation within the agribusiness sector, both theoretically and empirically, through an examination of Chinese A-share agriculture-related listed companies spanning from 2011 to 2021. The findings suggest that digital transformation significantly enhances innovation capability of agribusiness, while concurrently fostering improvements of its innovation quality. These results hold robust following an endogeneity test and a series of robustness tests. Our heterogeneity analysis found that digital transformation exerts a more pronounced influence on promoting innovation among state-owned agribusinesses, those located in the eastern region of China, and those facing heightened financing constraints. Mechanism testing revealed that digital transformation not only enhances the technological capabilities of agribusiness but also alleviates their financial constraints, thereby facilitating the convergence of innovative resources such as technology, talent and capital to agribusiness, and consequently elevating agribusi-ness innovation levels. This paper elucidates the impacts and mechanisms of digital transformation on agribusiness innovation, offering valuable insights for decision-makers aiming to foster agribusiness innovation, particularly in developing nations