Fish and chips and Apache Kafka®
07-21, 14:00–14:30 (Europe/Prague), Terrace 2A

Apache Kafka® is the de facto standard in the data streaming world for sending messages from multiple producers to multiple consumers, in a fast, reliable and scalable manner.

Come and learn the basic concepts and how to use it, by modelling a traditional British fish and chips shop!

Handling large numbers of events is an increasing challenge in our cloud centric world. For instance, in the IoT (Internet of Things) industry, devices are all busy announcing their current state, which we want to manage and report on, and meanwhile we want to send firmware and other updates back to specific groups of devices.

Traditional messaging solutions don't scale well for this type of problem. We want to guarantee not to lose events, to handle high volumes in a timely manner, and to be able to distribute message reception or production across multiple consumers or producers (compare to sharding for database reads).

As it turns out, there is a good solution available: Apache Kafka® - it provides all the capabilities we are looking for.

In this talk, rather than considering some imaginary IoT scenario, I'm going to look at how one might use Kafka to model the events required to run a traditional British fish and chip shop: ordering (plaice and chips for me, please), food preparation, accounting and so on.

I'll demonstrate handling of multiple producers and consumers, automatic routing of events as new consumers are added, persistence, which allows a new consumer to start consuming events from the past, and more.

Find the slides and demos on Aiven Labs

Expected audience expertise


After being a programmer for a good few years, I changed career in 2022 to become a Developer Educator at Aiven ( My favourite programming language is Python, my favourite markup language is reStructuredText, my favourite storage technologies are SQLite, PostgreSQL and Redis, and since joining AIven I've become all enthusiastic about Apache Kafka.
Find out more about my past at