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Why Systems Fail: From Ontology Modeling, Observability, and CMDB to AI-Agent Root Cause Investigation
Paperback
Publisher: Independently Published
Published: Aug 7 2026
Pages: 274
Weight: 0.74
Height: 0.68 Width: 6.00 Depth: 9.00
Language: English
- model services, resources, deployments, dependencies, telemetry, alerts, and incidents;
- use RDF, RDFS, OWL 2, SPARQL 1.1, and SHACL together;
- resolve identities across multiple data sources without hiding conflicts;
- represent time, provenance, confidence, and data quality;
- connect OpenTelemetry, ServiceNow CSDM, Backstage, Palantir Ontology, and metadata catalogs to a coherent semantic model;
- design evidence-bounded GraphRAG and AI-agent investigation workflows;
- test, version, govern, secure, and evolve an ontology in production. Each chapter includes a diagram, practical examples, exercises, and traceable sources. The book also provides a bilingual glossary, standards quick reference, an executable CMDB/observability case study, exercise answers, and a curated reading path. Written for platform engineers, SREs, observability teams, CMDB practitioners, data architects, knowledge-graph builders, and technical leaders who need systems to agree on what their data means.
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