Can we use machine learning to detect security threats in real-time? As organizations increasingly rely on distributed systems, it is becoming more important to analyze the traffic that passes through those systems quickly. Confluent Hackathon ’22 finalist, Géraud Dugé de Bernonville (Data Consultant, Zenika Bordeaux), shares how his team used TensorFlow (machine learning) and Neo4j (graph database) to analyze and detect network traffic data in real-time. What started as a research and development exercise turned into ZIEM, a full-blown internal project using ksqlDB to manipulate, export, and visualize data from Apache Kafka.

What is ksqlDB and how does Simon Aubury (Principal Data Engineer, Thoughtworks) use it to track down the plane that wakes his cat Snowy in the morning? Experienced in building real-time applications with ksqlDB since its genesis, Simon provides an introduction to ksqlDB by sharing some of his projects and use cases.

ksqlDB makes it easy to read, write, process, and transform data on Apache Kafka the de facto event streaming platform. With simple SQL syntax, pre-built connectors, and materialized views, ksqlDB’s powerful stream processing capabilities enable you to quickly start processing real-time data at scale. But how does ksqlDB work? In this episode, Michael Drogalis (Principal Product Manager, Product Management, Confluent) previews an all-new Confluent Developer course – Inside ksqlDB, where he provides a full overview of ksqlDB’s internal architecture and delves into advanced ksqlDB features.

Building a large, stateful Kafka Streams application that tracks the state of each outgoing email is crucial to marketing automation tools like Mailchimp. Joining us today in this episode, Mitch Seymour, staff engineer at Mailchimp, shares how ksqlDB and Kafka Streams handle the company’s largest source of streaming data.

Viktor Gamov (Developer Advocate, Confluent) returns to Streaming Audio to explain the magic of ksqlDB, ideal testing environments for ksqlDB, and the ksqlDB test runner. He also talks about the future of ksqlDB, the future of integration testing, and his favorite new feature among recent upgrades.