Transfers Hundreds of Terabytes of Data With CDC

Pinterest’s large-scale CDC implementation highlights how data engineering at massive scale demands both architectural discipline and operational automation. Their platform moves hundreds of terabytes per day from thousands of sharded MySQL sources into analytical systems using Kafka Connect and Debezium as the core data plane, with a dedicated control plane orchestrating shard discovery, offset tracking, connector lifecycle, and failure recovery.

The key insight is that throughput alone isn’t enough — resilience, consistency, and observability must be first-class concerns. By decoupling configuration and streaming logic, Pinterest can roll out connector updates safely, reroute partitions, and maintain exactly-once semantics even under heavy load. Metadata synchronization and idempotent replays prevent duplication during recovery, while internal tooling enforces schema evolution rules across teams.

For any large organization attempting continuous replication between transactional and analytical systems, Pinterest’s approach underlines the importance of treating CDC not as plumbing but as infrastructure — a managed, scalable service that balances latency, correctness, and operational simplicity at internet-company scale.

https://blog.bytebytego.com/p/how-pinterest-transfers-hundreds