- Tsinghua-Peidan - AIOps course in Tsinghua.
- 基于机器学习的智能运维
- 阿里全链路监控方案
- A Comparison of Mapping Approaches for Distributed Cloud Applications.
- 腾讯运维的AI实践
- AI 时代下腾讯的海量业务智能监控实践
- 织云Metis时间序列异常检测全方位解析
- 百度智能流量监控实战
- 搭建大规模高性能的时间序列大数据平台
- 异常检测：百度是这样做的
- Yahoo大规模时列数据异常检测技术及其高性能可伸缩架构
- Next Generation of DevOps AIOps in Practice @Baidu
- Tools to Monitor and Visualize Microservices Architecture
- python-fp-growth，挖掘频繁项集
- Anomaly Detection with Twitter in R
- 百度开源时间序列打标工具：Curve
- Microsoft开源时间序列打标工具: TagAnomaly
- Anomaly Detection Examples
- Survey on Models and Techniques for Root-Cause Analysis
- 基于机器学习的智能运维
- HotSpot: Anomaly Localization for Additive KPIs With Multi-Dimensional Attributes
- Chinese：清华AIOps新作:蒙特卡洛树搜索定位多维指标异常
- Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications. [Slide] [Github]
- Opprentice: Towards Practical and Automatic Anomaly Detection Through Machine Learning
- Robust and Rapid Clustering of KPIs for Large-Scale Anomaly Detection
- Alibaba/clusterdata
- Azure/AzurePublicDataset
- Google/cluster-data
- The Numenta Anomaly Benchmark(NAB)
- Yahoo: A Labeled Anomaly Detection Dataset
- 港中文loghub数据集
- 腾讯织云（腾讯的）
- 智能运维前沿（清华裴丹团队的）
- AIOps智能运维（百度的）
- 华为产品可服务能力（华为的）