MicroOps: Rapid Microservice Data Simulation and AIOps Model Development Platform

Yuewei Li, Zhigang Wang, Qi Qi, Yuhan Jing, Jinming Wu, Zhikang Wu, Yan Lu, Chengsen Wang, Xingyu Wang, Jingyu Wang

Abstract: Artificial Intelligence for IT Operations (AIOps) for microservice systems has attracted much attention in academia and industry, aiming to reduce the burden of operations developers and improve the reliability of microservices. However, due to mostly private datasets and unique data requirements of different studies, researchers are forced to invest considerable effort in tedious tasks such as data simulation and data collection, which prevents them from concentrating on model development. To tackle this dilemma, we introduce MicroOps, a microservice data simulation and AIOps model development platform. MicroOps provides full-process automation support for microservice AIOps research, with key roles for rapid dataset generation and intuitive model testing. Based on MicroOps, we release two multimodal datasets collected from two widely used microservice systems. A user survey is conducted on MicroOps, evaluating its usability and practicality through the System Usability Scale (SUS) and open-ended questions. The results show that both are highly positively rated. Platform: https://github.com/OpenNetAI/MicroOps.