Learn how the combination of Apache Kafka and Apache Flink is making stateful stream processing even more expressive and flexible to support applications in streaming that were previously not considered streamable.
The new world of applications and fast data architectures has broken up the database: Raw data persistence comes in the form of event logs, and the state of the world is computed by a stream processor. Apache Kafka provides a strong solution for the event log, while Apache Flink forms a powerful foundation for the computation over the event streams.
In this talk we discuss how Flink’s abstraction and management of application state have evolved over time and how Flink’s snapshot persistence model and Kafka’s log work together to form a base to build ‘versioned applications’. We will also show how end-to-end exactly-once processing works through a smart integration of Kafka’s transactions and Flink’s checkpointing mechanism.