Reimagining a data architecture to provide real-time data flow for sporting events can be complicated, especially for organizations with as much data as World Table Tennis (WTT). Vatsan Rama (Director of IT, ITTF Group) shares why real-time data is essential in the sporting world and how his team reengineered their data system in 18 months, moving from a solely on-premises infrastructure to a cloud-native data system that uses Confluent Cloud with Apache Kafka as its central nervous system.

Inheriting software in the banking sector can be challenging. Perhaps the only thing harder is inheriting software built by a committee of banks. How do you keep it running, while improving it, refactoring it, and planning a bigger future for it? In this episode, Jean-Francois Garet (Technical Architect, Symphony) shares his experience at Symphony as he helps it evolve from an inherited, monolithic, single-tenant architecture to an event mesh for seamless event-streaming microservices. He talks about the journey they’ve taken so far, and the foundations they’ve laid for a modern data mesh.

Security is a primary consideration for any system design, and Apache Kafka is no exception. Out of the box, Kafka has relatively little security enabled. Rajini Sivaram (Principal Engineer, Confluent, and co-author of “Kafka: The Definitive Guide” ) discusses how Kafka has gone from a system that included no security to providing an extensible and flexible platform for any business to build a secure messaging system. She shares considerations, important best practices, and features Kafka provides to help you design a secure modern data streaming system.

How does the JDBC connection work? And what could go wrong with it? When it comes to streaming database events into Apache Kafka, the JDBC connector usually represents the first choice for its flexibility and the ability to support a wide variety of databases without requiring custom code. As an experienced data analyst, Francesco Tisiot (Senior Developer Advocate, Aiven) delves into his experience of streaming Kafka data pipeline with JDBC source connector and explains what could go wrong. He discusses alternative options available to avoid these problems, including the Debezium source connector for real-time change data capture.

Setting up a reliable cloud networking for your Apache Kafka infrastructure can be complex. There are many factors to consider—cost, security, scalability, and availability. With immense experience building cloud-native Kafka solutions on Confluent Cloud, Justin Lee (Principal Solutions Engineer, Enterprise Solutions Engineering, Confluent) and Dennis Wittekind (Customer Success Technical Architect, Customer Success Engineering, Confluent) talk about the different networking options on Confluent Cloud, including AWS Transit Gateway, AWS, and Azure Private Link, and discuss when and why you might choose one over the other.