Event-sourcing allows the business to ask questions about your application's data that weren't thought of when the system was created, such as "how often are customers changing their shipping address?".

However, it requires a mind-shift from the well-known DDD Tactical Patterns (Aggregates and Repositories), but the benefits are more flexible systems, with a state-change trail that AI can leverage.

In this session, you'll learn how event-sourcing works at the code level without event-sourcing libraries getting in the way of deeper understanding. We'll walk through a codebase for a Concert Ticketing system and see how straightforward the implementation can be.

We start with "Event Modeling" the system, defining the commands (user actions) that generate them, the aggregates that make business decisions (and how to move to "deciders"), and the projections used to generate the user interface. We'll see how event-sourcing makes testing easier to write and understand.

We'll end by touching on the challenges to using event-sourcing, such as performance and schema evolution.