【AIOps 】最棒的中文AIOps

• Awesome AIOps
  • White Paper
  • Course and Slides
  • Industry Practice
  • Article
  • Tools and Algorithms
  • Paper
  • Dataset
  • Useful WeChat Official Accounts

White Paper

• 《企业级 AIOps 实施建议》白皮书

Course and Slides

• Tsinghua-Peidan - AIOps course in Tsinghua.
• 基于机器学习的智能运维

Industry Practice

• 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
• 腾讯织云Metis智能运维学件平台开源代码

• 阿里全链路监控方案
• 阿里开源4000台服务器真实数据集

• 百度智能流量监控实战
• 异常检测：百度是这样做的
• Next Generation of DevOps AIOps in Practice @Baidu [video]

• 搭建大规模高性能的时间序列大数据平台
• Yahoo大规模时列数据异常检测技术及其高性能可伸缩架构
• Netflix: Robust PCA
• LinkedIn: exponential smoothing
• Uber: multivariate non-linear model

Article

• 智能运维|AIOps中的四大金刚都是谁？
• A Comparison of Mapping Approaches for Distributed Cloud Applications
• AIOps探索：基于VAE模型的周期性KPI异常检测方法

Tools and Algorithms

• 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
• facebook/prophet, Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
• google/CausalImpact, An R package for causal inference in time series
• 时间序列分析之ARIMA
• 时间序列特征提取库tsfresh
• Yahoo EGADS : A Java package to automatically detect anomalies in large scale time-series data
• Awesome Time Series Analysis and Data Mining

Paper

• 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
• Opprentice: Towards Practical and Automatic Anomaly Detection Through Machine Learning
• Robust and Rapid Clustering of KPIs for Large-Scale Anomaly Detection
• KPI-TSAD: A Time-Series Anomaly Detector for KPI Monitoring in Cloud Applications
• Anomaly Detection Based on Mining Six Local Data Features and BP Neural Network
• Generic and Robust Localization of Multi-Dimensional Root Causes
• Papers from Tsinghua NetMan Lab

Dataset

• 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
• 2018 AIOPS挑战赛预赛测试集 2018 AIOPS挑战赛预赛训练集

Useful WeChat Official Accounts

• 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）

原文：https://github.com/linjinjin123/awesome-AIOps