A single automaton is activated. The ruleset for its potential state is predetermined. How many generations will it or its descendants take to breach the confines of their environment? What if hundreds had been activated?

Using a zero-player simulation with each automaton signalling its own state-change event to the server, we'll see how Exposed, a database access library, can assist with high throughput and the handling of asynchronous database operations. We'll also leverage Kotlin Flow on top of Exposed DSL queries to observe a continuous data stream of all state updates to the UI.

Throughout different phases of the simulation cycle, we'll query our data using Exposed, then analyze and transform it using Kotlin DataFrame, and visualize the results using the Kandy plotting library. Finally, we'll see how the new Exposed Gradle plugin can help simplify the process of migrating our database when we're ready to expand on our simulation's original dataset.