Betting platforms take many forms from traditional horse race betting to betting on sports games in real time. While previous betting interactions for these may have been more “batch-oriented” (i.e. a viewer places a bet before the race and receives their payout after), with accessible real-time data companies are able to create systems that utilize the events of the competition to create interactive bets. Take, for example, a horse race where the horse with the worst odds makes a remarkable comeback. If the horse happens to show the payouts are huge for the lucky few who decided to take a chance on the underdog. Imagine instead that the betting platform was able to reassess the horse’s odds as it made its advancement and offer the viewers the opportunity to cast bets for this horse in real time. This more sophisticated view of betting allows for companies to provide bets which are dynamic: creating a more exciting experience for the viewer and ultimately driving more revenue from the bets being placed.

Sami Ahmed and Amanda Gilbert, Solutions Engineers specializing in Confluent Cloud, will be diving deep into the logistics of creating such an application. In addition to sharing architecture recommendations to enable high performance, they will be demoing a system that leans on Confluent Cloud and Kafka Streams for its data in motion. Attendees will gain insight into building interactive systems, a skill which stretches beyond the gaming and betting industries alone.