chenryn/aiops-handbook resource

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1570 stars · 302 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated handbook collecting papers, conference slides, and open-source repositories about AIOps (Algorithmic IT Operations), organized by scenario categories from an industry whitepaper. It covers topics like KPI anomaly detection, metric monitoring, and related machine-learning approaches for IT operations.

Use cases

• find papers on KPI anomaly detection for IT operations
• discover open-source AIOps tools like Donut or Skyline
• learn how companies like Tencent, Alibaba, and Netflix approach anomaly detection
• research time-series anomaly detection algorithms for monitoring
• get started with AIOps concepts and implementation practices
• find datasets and competitions for metric anomaly detection

When to choose

• you need a curated starting point for AIOps research or tooling
• you want academic papers and real-world implementations side by side
• you are exploring anomaly detection for metrics and KPIs in operations

When to avoid

• you need a ready-to-run AIOps product rather than a reference collection
• you require English-only resources, as much of the handbook is written in Chinese
• you want executable code or a library rather than links and summaries

Facets

learning-resource · maturity active

monitoring machine-learning analytics developer-tools monitoring artificial-intelligence machine-learning analytics awesome-lists cross-platform aiops anomaly-detection kpi-monitoring curated-list papers slides time-series observability chinese-language devops

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