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Building an Interactive Betting Platform with Confluent Cloud

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.


Amanda Gilbert

Amanda Gilbert is a Senior Solutions Engineer for Confluent and a Confluent Cloud subject matter expert. She has been working in the data engineering space since graduating college in 2014. She is passionate about building event driven architectures that utilize existing technologies, limit technical debt and create performant applications. Amanda lives in Charlotte, NC where she enjoys playing poker, hiking, traveling and reading in her free time.

Sami Ahmed

Commercial Solutions Engineer at Confluent where our mission is to help our customers set data in motion.

Other recent experience: data scientist (contractor) working remotely for a NY-based startup, Saturn Cloud. I focused on demonstrating value/time saved from leveraging Saturn's distributed computing platform, using technologies like distributed Dask, GPUs, and Prefect. You can reference my Github or Medium below to see the Jupyter Notebooks and articles I produced while at Saturn. I was a technical support on sales calls, and regularly interfaced with engineering in testing new features and creating documentation for product releases. Prior to that, I was did business development at a seed fund in Hong Kong, Product Design at a small company in Portugal, Quality Assurance for a venture studio in Chicago, and a Presales role at the fastest U.S. startup to a $2B valuation.