一句话：报告作者所在软件编辑类中小企业基于开源工具搭建并落地本地部署 AIOps 基础设施的经验与选型依据。
本文针对现代软件系统运维中传统维护方式不足、商业 AIOps 方案成本高且存在数据治理和私有软件覆盖限制的问题，探讨中小企业采用开源工具实施本地部署 AIOps 的可行性。作者介绍了一套已在公司内部成功部署的 AIOps 基础设施，说明各组件设计选择及其理由，并重点分享数据管理系统选型标准、集成方式以及数据与事件管理挑战的应对经验。评估形式为经验报告，未展开量化基准，但总结了可复用的工程实践，供希望以现代 AIOps 方式内部管理软件维护流程的企业参考。
Information Technology has become a critical component in various industries, leading to an increased focus on software maintenance and monitoring. With the complexities of modern software systems, traditional maintenance approaches have become insufficient. The concept of AIOps has emerged to enhance predictive maintenance using Big Data and Machine Learning capabilities. However, exploiting AIOps requires addressing several challenges related to the complexity of data and incident management. Commercial solutions exist, but they may not be suitable for certain companies due to high costs, data governance issues, and limitations in covering private software. This paper investigates the feasibility of implementing on-premise AIOps solutions by leveraging open-source tools. We introduce a comprehensive AIOps infrastructure that we have successfully deployed in our company, and we provide the rationale behind different choices that we made to build its various components. Particularly, we provide insights into our approach and criteria for selecting a data management system and we explain its integration. Our experience can be beneficial for companies seeking to internally manage their software maintenance processes with a modern AIOps approach.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{BendimeradRMK23,
title = {On-Premise AIOps Infrastructure for a Software Editor SME: An Experience Report},
author = {Anes Bendimerad and Youcef Remil and Romain Mathonat and Mehdi Kaytoue},
booktitle = {FSE},
year = {2023},
doi = {10.1145/3611643.3613876}
}