Sami Ahmed
Solutions Engineer at Confluent (FSI-APAC)
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Sami is a Strategic Solutions Engineer at Confluent specializing in Financial Services (FSI). He leverages tools across the streaming technologies stack to help FSI companies realize their use cases, including realtime fraud detection applications, transactional systems, and bridge to cloud. He has worked with Globally Systemically Important Banks in the US and now serves Confluent's FSI customers within APAC. Before FSIs, he enabled data streaming use cases for small and medium-sized companies in various industries including healthcare, IoT, e-commerce, and aerospace.
To Poll, or Not to Poll: Choosing the Right Streaming Protocol for Your Application
You’ve decided to build a real-time application – great! Now which data streaming communication protocol is right for you – polling, websockets, or server sent events (SSE)? Furthermore, how do these protocols integrate with Kafka? How can you gracefully handle if/when your client disconnects from Kafka?
In this session, we will set the stage by talking about the strengths and weaknesses of each protocol, and then dive into how Kafka can be leveraged with these different protocols. We will demo different approaches you might take, for example using a Kafka connector with SSE vs. just having a client handle these real-time workloads directly – and also perform some chaos testing to test resiliency.
By the end of this session, you should have an understanding of these different streaming protocols at your disposal, and how to select the appropriate one for your application.
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.
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