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.

New Relic runs one of the larger Apache Kafka installations in the world, ingesting circa 125 petabytes a month, or approximately three billion data points per minute. Anton Rodriguez is the chief architect of the system, responsible for hundreds of clusters and thousands of clients, some of them implemented in non-standard technologies. In addition to the large volume of servers, he works with many teams, which must all work together when issues arise.

Confluent Platform 7.1 expands upon its already innovative features, adding improvements in key areas that benefit data consistency, allow for increased speed and scale, and enhance resilience and reliability. Following the standard for every Confluent release, Confluent Platform 7.1 is built on the most recent version of Apache Kafka 3.1, including KIP-768: extend SASL/OAUTHBEARER with support for OIDC, KIP-773: Differentiate consistently metric latency measured in mills and nanos, as well as KIP-775: Custom partitioners in foreign-key-joins.

Scaling Apache Kafka can be tricky, let alone scaling a team. When he was first hired, Domenico Fioravanti of Therapie Clinic was given the challenging task of assembling a sizable tech team from scratch, while simultaneously building a scalable and decoupled architecture from the ground up. In addition, he wanted to deliver value to the company from day one. One way that Domenico ultimately accomplished these goals was by focusing on managed solutions in order to avoid large investments in engineering know-how. Another way was to deliver quickly to production by using the existing knowledge of his team.

What is GraphQL? And how can you combine GraphQL with Apache Kafka to query data in real time? With over 10 years of experience as a backend engineer, Gerard Klijs is a Confluent Community Catalyst, a contributor to the GraphQL project, and also a creator and maintainer of a Rust library to use Confluent Schema Registry with Java client. In this episode, he explains why you want to use Kafka with GraphQL and how they work together to bridge the gap between backend and frontend to make data more easily accessible in the frontend.