Agent-Assisted Schema Evolution
Automating backwards-compatible schema evolution could recover almost $4 million in engineering capacity for a typical tech platform company.
Schema Evolution & Compatibility Types | Backward, Forward, Full, Transitive
docs.confluent.ioSchema Registry schema evolution and compatibility types: backward compatibility (consumers can read old data), forward compatibility (producers write old format), full compatibility (both), transitive modes, default compatibility settings, and compatibility groups for Avro, JSON Schema, and Protobuf.
Understanding Avro Compatibility
Digging into the different compatibility levels of Avro that can be used and what they actually mean.
Understanding Schemas and Message Types in Enterprise Data Integration
Exploring OpenAPI, AsyncAPI, CloudEvents, Schema Registry, OpenTelemetry Semantic Conventions, EDI, and More - A Learning Resource for Technical Product Managers
"Change Data Capture Breaks Encapsulation". Does it, though?
This post originally appeared on the Decodable blog. All rights reserved. Having worked on Debezium—an open-source platform for Change Data Capture (CDC)—for several years, one concern I’ve heard …
“Change Data Capture Breaks Encapsulation”. Does it, though?
When—and when not—CDC can break encapsulation, whether it matters, and strategies for avoiding these problems when it does happen.