Modern businesses have data at their core, and this data is changing continuously. Stream processing is what allows you to harness this torrent of information in real-time, and thousands of companies use Apache Kafka as the de-facto event streaming platform to transform and reshape their industries. Whether you know it or not: many of your daily activities such as shopping online, listening to music, booking a hotel, driving a car, making payments, staying in touch with friends on social networks, and reading a newspaper are powered by Apache Kafka behind the scenes. Example companies include Apple, Netflix, Microsoft, Paypal, Audi, Uber, CERN, New York Times, AirBnB, Etsy, Zalando, Pinterest, and the BBC.
In this talk we will introduce Apache Kafka, a distributed, highly scalable, fault-tolerant platform for event streaming. We discuss use cases as we as some of the internals of Kafka, such as its data and processing model, and how it achieves elasticity, scalability, and fault-tolerance. More specifically, we cover the core of Kafka, i.e. its storage and publish/subscribe layer, as well as its data integration component Kafka Connect, and the processing technologies Kafka Streams (for Java and Scala applications) and KSQL, the streaming SQL engine for Kafka.
