Event Driven

Reference Architecture: Redis + Kafka for Fast Reads and Event Propagation 1. Purpose This document describes a reference architecture where: Redis is used to accelerate synchronous read paths Kafka is used to propagate state changes asynchronously The application layer is the sole coordinator of state and events This architecture optimises for: Low latency API responses Decoupled downstream processing Independent scaling of consumers Eventual consistency across systems It does not assume microservices, CQRS, or event sourcing by default. ...

Redis + Kafka: Fast Reads with Event-Driven Change Propagation Overview Redis and Kafka are often presented together, yet they solve orthogonal problems: Redis optimises synchronous access to current state Kafka propagates asynchronous state changes to interested consumers Used together, they enable: Low-latency API responses Decoupled distribution of data changes Independent scaling of read paths and consumers This article explains how they complement each other in practice, without implying any direct coupling or “magic integration”. ...