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If you’re using an Android device, you can download the BetWinner APK for Android. By default, each Kafka topic has six partitions; you don’t really need all the six partitions for this demo, but in a real-life scenario, adding more partitions is the primary way to increase Kafka capacity so you can deal with high load. Payment processing is not demonstrated here, but in a complete system, this would allow you to accept late bets if the risk isn’t too high. Here, we now take you to an app review of the bookmakers in India’s online betting platform. That allows consumers to view odds and create bets on the content site and then, with a click, enter the betting app to submit the wager. Once you’ve clicked the Betting view button, you will be taken to the second screen, where you can see a list of cars with changing odds that you can bet on. As mentioned before, ksqlDB is used to create a materialized view of the bets placed, and to push updated odds into the Odds topic in Confluent Cloud. DB allows you to create materialized views, and continuously transform, enrich, join together, and aggregate events.
Together, Confluent and Ably enable you to stream and process high volumes of data in your backend Kafka pipeline, and then broadcast messages in milliseconds to very high and quickly changing numbers of client devices at the network edge, in a fault-tolerant manner, without any update being delivered in the wrong order or more than once. How do you decide which rollover is good and which rollover is too high? Some bookmakers somewhat restrict themselves in terms of what odds they provide, but Swiftbet are very good when it comes to Australian horse racing, offering top tote odds on all races, which is outstanding. Decimal odds are not often seen in the North American sports betting space, but some online sportsbooks will have a feature where you can toggle how odds appear. It’s also an enterprise-only feature. Note that the Kafka rule is a new feature, and it’s currently in developer preview. Note that for testing push notifications, you will have to create a Firebase Cloud Messaging account, and set up Ably and Firebase accordingly-read the tutorial for details.
Note that Confluent gives you the flexibility to select the cloud provider and region of your choice to deploy the Kafka cluster. Once you’ve logged in to Confluent Cloud, create a Kafka cluster (default settings are OK for the purpose of this demo). Now that you have a Kafka cluster and topics up and running, set up a basic ksqlDB application. However, Ably channels are provisioned dynamically at the point of use (there’s no need to pre-provision them ahead of time), and they have hierarchical namespaces to enable rule-based processing of messages (e.g., push notifications, firehose rules). Each of these events contains information about when the bet was placed, and the odds at that time. Now if you go to the Dev console tab of the Ably app you created earlier, you should see the list of bets placed updating in real time. You’ll see other familiar bets updating as the downs go on, like over/unders and total points for each team. This lets you see the likely outcome of any match or event easily.
Confluent Cloud enables you to effortlessly scale to as many topics as you need, each one storing specific event data (like the list of fixtures), and using Schema Registry to safeguard data formatting. Although the PoC covered in this blog post relates to gaming and betting, you can easily combine Confluent Cloud and Ably to deliver scalable real-time digital experiences for a wide variety of use cases and industries, from real-time asset tracking and virtual events to healthcare and EdTech. So far, this article has demonstrated the feasibility of using Confluent Cloud and Ably to power real-time betting experiences. If you don’t have one yet, start by signing up for a Confluent Cloud account. Next, log in to your Ably account dashboard and create an Ably app. The company expects to roll out its app in the state this summer, contingent on the approval of the Colorado Division of Gaming. So let’s check out factors for the review in India. There are many possible types of bets out there. Due to push notifications being occasional batch jobs, they are less well-suited to a direct streaming integration between Confluent and Ably. So this demo uses a Python microservice that queries ksqlDB via REST, and sends push notifications through Ably.
