# chenryn/aiops-handbook

Collection of slides, repositories, papers about AIOps

Repository: https://github.com/chenryn/aiops-handbook
Canonical: https://ross.abutalabs.com/products/aiops-handbook
License: Apache-2.0
License Family: permissive
Topics: aiops, kpi, anomalydetection
Last push: 2026-03-17T03:17:07+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 72, release rhythm 35, longevity 100
- inputs: {"age_days": 2949, "days_push": 169, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1570, forks 302 (observed 2026-08-28T04:05:05.359224+00:00)

## What it is
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
- artifact type: learning-resource
- maturity: active
- function: monitoring, machine-learning, analytics, developer-tools
- domain: monitoring, artificial-intelligence, machine-learning, analytics, awesome-lists
- platform: cross-platform
- tags: aiops, anomaly-detection, kpi-monitoring, curated-list, papers, slides, time-series, observability, chinese-language, devops

## Member repositories
- chenryn/aiops-handbook (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:05.359224+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:58:28.235134+00:00, confidence not recorded.
  - readme: https://github.com/chenryn/aiops-handbook (fetched 2026-08-28T04:05:05.359224+00:00, sha fe28c0e3ebe7)
- Data as of 2026-08-30T08:39:29.467469+00:00.