Spring Into Confluent Cloud with Kotlin – Part 2: Kafka Streams

This webinar focuses on protecting sensitive data using CSFLE (Confluent Schema for Format and Language Enforcement) with Spring Framework, Confluent Cloud, and the Kotlin language. It explores how to create Kafka Streams topologies that persist results in a state store, allowing for querying of counts for specific words. The presentation also delves into joining streams of typed data using Avro schemas, demonstrating how to track check-in events for high-level members with enriched check-in events. Throughout the webinar, Kotlin's concise syntax and null safety features are highlighted as advantages over Java in building APIs and topologies. The demonstration showcases how to write unit tests for Kafka Streams topologies, including testing for known and unknown member cases, using JUnit 5's @ParameterizedTest annotation.

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