AIOps Engineering Handbook

Production-grade reference for building Autonomous Intelligent Operations on AWS, Kubernetes, and cloud-native stacks.

Languages	Tiếng Việt · English
Chapters	System Foundations S/S2 · shared sequence 00–17 · Vietnamese production/capstone extension 18–21
Repo	github.com/XUanhoa04/aiops-engineering-handbook
Curriculum	CURRICULUM.md

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Architecture

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Learning path

graph LR
    SF[S-S2 System Foundations] --> A[00-01 Foundation]
    A --> B[02-05 Collect]
    B --> C[06 Data plane]
    C --> D[07 Kafka]
    D --> H[08 Topology + Change]
    H --> E[09-13 Intelligence + Action]
    E --> F[14 Production]
    F --> G[15-17 Reuse + Replay]
    G --> I[18 Predictive Ops]
    I --> J[19 Incident Ops]
    J --> K[20 Governance]
    K --> L[21 End-to-End Closed Loop]
    H --> C

1. System foundations — Core mechanics (S), then advanced failure and evidence reasoning (S2)
2. Foundation — Why AIOps, observability thinking
3. Collect — OTel, Prometheus, Loki, Tempo
4. Data plane — Normalize, enrich, store, feature store (when to use)
5. Transport — Kafka
6. Topology & change — Graph + deploy/change bus feeding enrichment and intelligence
7. Intelligence + action — Detect → correlate → RCA → investigate → remediate
8. Production + reuse — Production engine, patterns, domain packs and benchmark replay
9. Proactive operations + governance — Predict capacity risk, coordinate incidents and control AI authority
10. End-to-end capstone — Follow telemetry through baseline, detection, incident, RCA, safe remediation, verification and audit

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Start reading

Tiếng Việt

• S — System Fundamentals
• S2 — System Fundamentals Next
• 00 — Giới thiệu
• 06 — Data Plane
• 08 — Topology & Change
• 18 — Predictive Operations
• 19 — Incident Operations
• 20 — Governance & Model Risk
• 21 — AIOps End-to-End Closed Loop

English

• 00 — Introduction
• 06 — Data Plane
• 08 — Topology & Change

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Local build

pip install -r requirements-docs.txt
mkdocs serve
# open http://127.0.0.1:8000

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