Building ML features at scale shouldn’t require every ML Scientist to become an expert in Spark or Flink. At Adyen, the Feature Platform team built a Python-based DSL that lets data scientists define features declaratively — while automatically generating the necessary batch or real-time pipelines behind the scenes.

Using a Raspberry Pi and a powerful trio of open-source technologies—Apache Kafka, Apache Flink, and Apache Iceberg—learn how to build a custom on-air sign to signal when you're on a call and discover how this same scaffolding can be scaled for millions of users.