Summary
This blog post discusses Pinterest's automated schema evolution framework, which improves the management of evolving schemas in their ingestion platform built on Kafka, Flink, Spark, and Iceberg. It details the challenges of schema evolution, highlights the solution's automated processes, SLA-based strategies, and the architecture used to ensure consistency and reliability across the ingestion pipeline. The authors emphasize a phased approach to schema changes that minimizes operational risk while ensuring correctness and outlines future goals of achieving zero-gap schema evolution.