Sarthak Jain

Schema Registry is the backbone of safe schema evolution and efficient data transfer in the Kafka ecosystem. Our data infrastructure spans online APIs (gRPC/Rest.li), databases (MySQL/Oracle/Espresso/TiDB), and powerful streaming and ingestion frameworks built on Kafka. From real-time ETL to OLAP systems like Pinot, from tracking and metrics pipelines feeding into Hadoop, to offline jobs pushing insights into derived stores like Venice; Kafka is the key cog in our data flywheel. As data moves through LinkedIn’s ecosystem, it traverses multiple schema languages and serialization formats, evolving—sometimes seamlessly, sometimes with transformation. But what happens when an upstream schema change inadvertently breaks downstream systems? Traditional siloed validation falls short, leading to data corruption, operational disruptions, and painful debugging. Join us as we dive into LinkedIn’s Universal Schema Registry (USR) solution for seamless, large-scale schema validation. 1. End-to-End Schema Compatibility – USR validates schemas holistically across RPC, Kafka, Espresso, Venice, and more, safeguarding the entire data lineage. 2. CI-Integrated Early Validation – A shift-left approach…