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AIOps Roadmap

Applying ML to operational telemetry to reduce alert noise and speed up root-cause analysis.

Estimated time:3–4 months

1🌱

Phase 1 — Observability Foundations

Alerting basics & alert fatigue causes

Service dependency/topology mapping

2📊

Statistical baselining (seasonal, rolling)

Time-series anomaly detection models

Log anomaly/pattern clustering

False-positive tuning

3🔍

Event correlation & deduplication

Topology-aware causal analysis

Change-event correlation (deploys/config)

Ranked-evidence incident summaries

4⚙️

advanced

Tiered automation (auto vs approval-required)

Playbook design with rate limits & rollback

Audit logging for automated actions

Human-in-the-loop escalation design

Begin with interview questions to assess your current level.