This article is reproduced from GitHub: https://github.com/linjinjin123/awesome-AIOps
White Paper
Course and Slides
- Tsinghua-Peidan - AIOps course in Tsinghua.
- Intelligent operation and maintenance based on machine learning
Industry Practice
- AI Practice of Tencent Operation and Maintenance
- Tencent's massive business intelligent monitoring practice in the AI era
- Zhiyun Metis time series anomaly detection comprehensive analysis
- Tencent Zhiyun Metis intelligent operation and maintenance learning software platform open source code
- Baidu Smart Traffic Monitoring Actual Combat
- Anomaly detection: Baidu does this
- Next Generation of DevOps AIOps in Practice @Baidu [video]
- Build a large-scale high-performance time series big data platform
- Yahoo large-scale time series data anomaly detection technology and its high-performance scalable architecture
- Netflix: Robust PCA
- LinkedIn: exponential smoothing
- Uber: multivariate non-linear model
Article
- Smart Operation|Who are the four King Kong in AIOps?
- A Comparison of Mapping Approaches for Distributed Cloud Applications
- AIOps Exploration: Periodic KPI anomaly detection method based on VAE model
Tools and Algorithms
- Tools to Monitor and Visualize Microservices Architecture
- python-fp-growth, mining frequent itemsets
- Anomaly Detection with Twitter in R
- Baidu open source time series marking tool: Curve
- Microsoft open source time series marking tool: 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
- ARIMA for time series analysis
- Time series feature extraction library tsfresh
- Awesome Time Series Analysis and Data Mining
Paper
- Survey on Models and Techniques for Root-Cause Analysis
- Intelligent operation and maintenance based on machine learning
- HotSpot: Anomaly Localization for Additive KPIs With Multi-Dimensional Attributes
- 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
- Hong Kong Chinese loghub dataset
Useful WeChat Official Accounts
- Tencent Zhiyun (Tencent's)
- Frontier of Intelligent Operation and Maintenance (by Pei Dan team of Tsinghua University)
- AIOps intelligent operation and maintenance (Baidu's)
- Serviceability of Huawei products (Huawei)
- Know the column: Intelligent Operation and Maintenance (AIOps)
Special statement: This article is transferred from github , thanks to linjinjin123 for the summary
White Paper
Course and Slides
- Tsinghua-Peidan - AIOps course in Tsinghua.
- Intelligent operation and maintenance based on machine learning
Industry Practice
- AI Practice of Tencent Operation and Maintenance
- Tencent's massive business intelligent monitoring practice in the AI era
- Zhiyun Metis time series anomaly detection comprehensive analysis
- Tencent Zhiyun Metis intelligent operation and maintenance learning software platform open source code
- Baidu Smart Traffic Monitoring Actual Combat
- Anomaly detection: Baidu does this
- Next Generation of DevOps AIOps in Practice @Baidu [video]
- Build a large-scale high-performance time series big data platform
- Yahoo large-scale time series data anomaly detection technology and its high-performance scalable architecture
- Netflix: Robust PCA
- LinkedIn: exponential smoothing
- Uber: multivariate non-linear model
Article
- Smart Operation|Who are the four King Kong in AIOps?
- A Comparison of Mapping Approaches for Distributed Cloud Applications
- AIOps Exploration: Periodic KPI anomaly detection method based on VAE model
Tools and Algorithms
- Tools to Monitor and Visualize Microservices Architecture
- python-fp-growth, mining frequent itemsets
- Anomaly Detection with Twitter in R
- Baidu open source time series marking tool: Curve
- Microsoft open source time series marking tool: 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
- ARIMA for time series analysis
- Time series feature extraction library tsfresh
- Awesome Time Series Analysis and Data Mining
Paper
- Survey on Models and Techniques for Root-Cause Analysis
- Intelligent operation and maintenance based on machine learning
- HotSpot: Anomaly Localization for Additive KPIs With Multi-Dimensional Attributes
- 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
- Hong Kong Chinese loghub dataset
Useful WeChat Official Accounts
- Tencent Zhiyun (Tencent's)
- Frontier of Intelligent Operation and Maintenance (by Pei Dan team of Tsinghua University)
- AIOps intelligent operation and maintenance (Baidu's)
- Serviceability of Huawei products (Huawei)
- Know the column: Intelligent Operation and Maintenance (AIOps)
Special statement: This article is transferred from github , thanks to linjinjin123 for the summary