This post discusses Event Sourcing in the context of Apache Kafka, examining the need for a single source of truth that spans entire service estates. The concept of notification via a broker breaks down complex call graphs, allowing processes to decouple themselves from one another. Events are facts that evolve and tell a story, forming a single source of truth. Implementing event sourcing in Kafka is a no-op if you've taken the event-driven approach, as events are simply written as they occur. The advantage of this 'database-fronted' approach is it provides a consistency point: you write through it into Kafka, meaning you can always read your own writes. Event sourcing is often used with Memory Images, which provide an optimal combination of fast, in-process reads and write performance far faster and more scalable than a typical database. The log breeds extensibility, empowering bootstrapping new services and migrating away from legacy systems.