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Netflix builds an observability ontology and RDF knowledge graph
Source:Shao Meng
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Oct 24
Shao Meng
Netflix builds an observability system with an ontology and RDF knowledge graph to support AutoRCA troubleshooting
Netflix built the Observability Ontology and the RDF knowledge graph QuipuDB, using type constraints to turn non-deterministic outputs from LLMs, fuzzy matching, and the like into deterministic triples that can be queried with SPARQL, which are then fed to AutoRCA. The graph covers about 12 namespaces, and Application is validated against a software catalog of about 49,000 entries; the Correlation Engine reads 13 types of signals and, within a window of about 10 minutes, finds paths by temporal proximity and severity, discarding correlation chains with confidence below 0.6. The author also summarizes eight principles for building your own, and mentions plans to next integrate with Upper, the domain modeling language of Netflix UDA.