Many modern video games are constantly evolving post-release. New maps, game modes, and game balancing adjustments are rolled out, often on a weekly basis. This continuous iteration to improve player engagement and satisfaction requires data-driven decision making based on events and telemetry captured during gameplay, and from community forums and discussions.
In this session you will learn how OpenShift Streams for Apache Kafka and Kafka Streams can be used to analyze real-time events and telemetry reported by a game server, using a practical example that encourages audience participation. Specifically you’ll learn how to:
Provision Kafka clusters on OpenShift Streams for Apache Kafka.
Develop a Java application that uses Kafka Streams and Quarkus to process event data.
Deploy the application locally, or on OpenShift and connect it to your OpenShift Streams for Apache Kafka Cluster.