Far from a controversial choice, Kafka is now a technology developers and architects are adopting with enthusiasm. And it’s often not just a good choice, but a technology enabling meaningful improvements in complex, evolvable systems that need to respond to the world in real time. But surely it's possible to do wrong! In this talk, we'll look at common mistakes in event-driven systems built on top of Kafka: - Deploying Kafka when an event-driven architecture is not the best choice. - Ignoring schema management. Events are the APIs of event-driven systems! - Writing bespoke consumers when stream processing is a better fit. - Using stream processing when you really need a database. - Trivializing the task of elastic scaling in all parts of the system. It's highly likely for medium- and large-scale systems that an event-first perspective is the most helpful one to take, but it's early days, and it's still possible to get this wrong. Come to this talk for a survey of mistakes not to make.