Microservices: Rethinking the Way We Treat Data and Services | Confluent

What this post added

This post introduces the concept of the 'Data Dichotomy' in microservices, where services aim to encapsulate data while data systems aim to expose it. It argues that traditional approaches to sharing data between microservices (service interfaces, messaging, shared databases) are insufficient. The post proposes event-driven architectures, specifically leveraging distributed logs like Kafka, as a solution. It highlights Kafka's ability to provide retentive, scalable streams and enable stateful stream processing within consuming services, thereby addressing the data dichotomy and facilitating independent service evolution.