🚀 Thrilled to continue my series, "Getting Started with Real-Time Streaming in Kotlin"!
The second installment, "Kafka Clients with Avro - Schema Registry and Order Events," is now live and takes our event-driven journey a step further.
In this post, we level up by:
* Migrating from JSON to Apache Avro for robust, schema-driven data serialization.
* Integrating with Confluent Schema Registry for managing Avro schemas effectively.
* Building Kotlin producer and consumer applications for Order events, now with Avro.
* Demonstrating the practical setup using Factor House Local and Kpow for a seamless Kafka development experience.
This is post 2 of 5 in the series. Next up, we'll dive into Kafka Streams for real-time processing, before exploring the power of Apache Flink!
Check out the full article:
https://jaehyeon.me/blog/2025-05-27-kotlin-getting-started-kafka-avro-clients/