A Scenario-Oriented Benchmark for Assessing AIOps Algorithms in Microservice Management
Abstract
AIOps algorithms play a crucial role in the maintenance of microservice systems. Many previous benchmarks' performance leaderboard provides valuable guidance for selecting appropriate algorithms. However, existing AIOps benchmarks mainly utilize offline datasets to evaluate algorithms. They cannot consistently evaluate the performance of algorithms using real-time datasets, and the operation scenarios for evaluation are static, which is insufficient for effective algorithm selection. To address these issues, we propose an evaluation-consistent and scenario-oriented evaluation framework named MicroServo. The core idea is to build a live microservice benchmark to generate real-time datasets and consistently simulate the specific operation scenarios on it. MicroServo supports different leaderboards by selecting specific algorithms and datasets according to the operation scenarios. It also supports the deployment of various types of algorithms, enabling algorithms hot-plugging. At last, we test MicroServo with three typical microservice operation scenarios to demonstrate its efficiency and usability.
Cite
@article{arxiv.2407.14532,
title = {A Scenario-Oriented Benchmark for Assessing AIOps Algorithms in Microservice Management},
author = {Yongqian Sun and Jiaju Wang and Zhengdan Li and Xiaohui Nie and Minghua Ma and Shenglin Zhang and Yuhe Ji and Lu Zhang and Wen Long and Hengmao Chen and Yongnan Luo and Dan Pei},
journal= {arXiv preprint arXiv:2407.14532},
year = {2024}
}
Comments
Codes are available at https://github.com/MicroServo/microservo, datasets are available at https://github.com/MicroServo/hot-plugging