Streaming Audio: A Confluent Podcast about Apache Kafka

What’s your favorite podcast? In celebration of International Podcast Day, Kris Jenkins invites 12 experts from the Apache Kafka community to talk about their favorite podcasts. Unlike other episodes where guests educate developers and tell stories about Kafka, its surrounding technological ecosystem, or the Cloud, this special episode provides a glimpse into what these guests have learned through listening to podcasts that you might also find interesting.

How do you build an event-driven application that can react to real-time data streams as they happen? Kris Jenkins (Senior Developer Advocate, Confluent) will be hosting another fun, hands-on programming workshop—Coding in Motion: Watching the River Flow, to demonstrate how you can build a reactive event streaming application with Apache Kafka, ksqlDB using Python.

Processing real-time event streams to identify wildlife movement patterns and population changes is a challenge but can be broken down into solvable problems. With a day job designing and building highly available distributed data systems, Simon Aubury (Principal Data Engineer, Thoughtworks) believes stream-processing thinking can be applied to any stream of events. In this episode, he shares his Confluent Hackathon ’22 winning project—a wildlife monitoring system to observe population trends over time using a Raspberry Pi, along with Apache Kafka, Kafka Connect, ksqlDB, TensorFlow Lite, and Kibana. He used the system to count animals in his Australian backyard and perform trend analysis on the results. Simon also shares ideas on how you can use these same technologies to help with other real-world challenges.

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.

How do you plan Apache Kafka capacity and Kafka Streams sizing for optimal performance? When Jason Bell (Principal Engineer, Dataworks and founder of Synthetica Data), begins to plan a Kafka cluster, he starts with a deep inspection of the customer's data itself—determining its volume as well as its contents: Is it JSON, straight pieces of text, or images? He then determines if Kafka is a good fit for the project overall, a decision he bases on volume, the desired architecture, as well as potential cost.