How do you analyze Reddit sentiment with Apache Kafka and microservices? Bringing the fresh perspective of someone who is both new to Kafka and the industry, Shufan Liu, nascent Developer Advocate at Confluent, discusses projects he has worked on during his summer internship—a Cluster Linking extension to a conceptual data pipeline project, and a microservice-based Reddit sentiment-analysis project. Shufan demonstrates that it’s possible to quickly get up to speed with the tools in the Kafka ecosystem and to start building something productive early on in your journey.

In this episode, Bobby Calderwood, founder of Evident Systems and creator of oNote explains event modeling—a converse approach to the reductive data model system. Event model system is enabled by tools like Apache Kafka, which effectively saves every bit of activity generated by the data system.

What is event sourcing, and how does it work? Event sourcing is often used interchangeably with event-driven architecture and event stream processing. However, Anna McDonald (Principal Customer Success Technical Architect, Confluent) explains it's a specific category of its own—an event streaming pattern.

Automated behavioral-driven testing of your event-driven microservices—sounds great, right? But how do you do it? SmartBear's Alianna Inzana shares about just that and some tooling that SmartBear makes to support efforts like this. In fact, SmartBear is actually responsible for many products that you're probably familiar with.

Nationwide Building Society, a financial institution in the United Kingdom with 137 years of history and over 18,000 employees, relies on Apache Kafka for their event streaming needs. But how did this come to be? In this episode, Tim Berglund talks with Rob Jackson (Principal Architect, Nationwide) about their Kafka adoption journey as they celebrate two years in production.