Netflix's Saish Sali, Nipun Kumar, and Sura Elamurugu describe the Metadata Service (MDS), a graph layer built to connect siloed ML tooling (model registry, pipeline orchestrator, experimentation platform, feature store, dataset platform, identity) across personalization, studio, payments, and ads.
The system assigns every ML asset a global AIP URI, ingests thin change events from each source over Kafka and SNS/SQS, then hydrates the full state from the source of truth so out-of-order or dropped events self-correct, with Datomic holding entities and reified edges and Elasticsearch powering search.
Background enrichment jobs walk multi-hop chains (model to pipeline run to A/B test cell to experiment) to materialize cross-system relationships, turning queries like "which experiments are running this model" or impact analysis on a feature change into a single graph traversal.
