In this episode, Kris interviews Doron Porat, Director of Infrastructure at Yotpo, and Liran Yogev, Director of Engineering at ZipRecruiter (formerly at Yotpo), about their experiences and strategies in dealing with data modeling at scale.

In principle, data mesh architecture should liberate teams to build their systems and gather data in a distributed way, without having to explicitly coordinate. Data is the thing that can and should decouple teams, but proper implementation has its challenges. In this episode, Kris talks to Florian Albrecht (Solution Architect, Hermes Germany) about Galapagos, an open-source DevOps software tool for Apache Kafka® that Albrecht created with his team at Hermes, a German parcel delivery company.

What are useful practices for migrating a system to Apache Kafka and Confluent Cloud? Picnic, an online-only, European grocery store that processes around 45 million customer events and five million internal events daily. An underlying goal at Picnic is to try and make decisions as data-driven as possible. In this episode, Dima Kalashnikov (Technical Lead, Picnic Technologies) shares several reasons for their recent migration to Confluent Cloud for better data analytics.

Event-driven architecture has taken on numerous meanings over the years—from event notification to event-carried state transfer, to event sourcing, and CQRS. Why has event-driven programming become so popular, and why is it such a topic of interest? Simon Aubury (Principal Data Engineer, ThoughtWorks) is here to tell all, including his own experiences adopting event-driven technologies and common blunders when working in this area.

Bobby Calderwood, the founder of Evident Systems, discusses event streaming, event modeling, and event-driven architecture.