《awesome-AIOps》

awesome-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

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

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）

全文完

awesome-AIOpsWhite PaperCourse and SlidesIndustry PracticeArticleTools and AlgorithmsPaperDatasetUseful WeChat Official Accounts

《awesome-AIOps》

原文：https://www.cnblogs.com/cx2016/p/13211308.html