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fault-correlation/README.md

Fault Correlation — Telecom Network Fault Correlation & Ticket Routing Automation

Fault Correlation

Telecom Network Fault Correlation & Ticket Routing Automation
A production-focused engineering reference for turning raw network telemetry into routed, SLA-aligned incidents.

🌐 Read it at faultcorrelation.org »


What this is

faultcorrelation.org is a deep, hands-on reference for the engineers who keep carrier networks running. It documents the full automation pipeline — from SNMP, syslog, and streaming telemetry ingestion, through deterministic correlation and topology-aware root-cause analysis, to automated, deduplicated, SLA-aligned ticket routing into ServiceNow, Jira, and Remedy.

Every page pairs architectural reasoning with runnable, production-grade Python — async asyncio pipelines, Pydantic V2 validation, and concrete numbers for the metrics operations teams actually live by (MTTA, MTTR, p99 latency, false-positive rate). No hand-waving, no toy examples: the code is written to drop into a real collector or correlation service.

Who it's for

  • NOC engineers who want to move from reactive alarm-watching to proactive, auditable automation.
  • Telecom operations teams standardizing multi-vendor telemetry into one event contract.
  • Python automation developers building ingestion, correlation, and ITSM integration services.
  • Platform / DevOps teams who need deterministic, schema-consistent inputs before correlation can begin.

What you'll find

The material is organized into four connected areas, each with focused topics and step-by-step implementation guides:

Area What it covers
Core Architecture & Log Taxonomy The reference model for ingesting, normalizing, and routing multi-vendor telemetry — event schema design, SNMP trap standardization, syslog parsing, timestamp normalization, and security boundaries.
Ingestion & Parsing Workflows The high-velocity data plane — edge collection, rate limiting, streaming gNMI/gRPC collectors, async batch processing, and error categorization with dead-letter handling.
Fault Correlation & Rule Engines The decision fabric — cross-source event linking, topology-aware correlation, severity scoring, temporal windowing, and threshold tuning that turn event storms into routed work items.
Ticket Routing & ITSM Automation The automation handoff — ITSM ticket payloads for ServiceNow, Jira, and Remedy, SLA-tiered escalation routing, and idempotent, deduplicated incident creation.

Why it stands out

  • Real code, not pseudocode. Async-first Python you can adapt directly, with inline commentary explaining the telecom-specific logic.
  • Carrier-scale thinking. Backpressure, storm suppression, exactly-once semantics, and dead-letter strategies are treated as first-class concerns.
  • Standards-grounded. References to the relevant IETF and ITU-T fault-management standards where they matter.
  • Fast and accessible. A static, dependency-light site tuned for performance and WCAG 2 AA accessibility.

Built with

  • Eleventy static site generator
  • Hand-authored, theme-aware inline SVG diagrams
  • Deployed on Cloudflare

Explore

www.faultcorrelation.org

Start with any area above, then follow the Related links at the foot of each page to move through the pipeline the way an event does — from the network edge to a routed ticket.

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