Speaker Details

Kate Stanley

IBM

Katherine Stanley is a Software Engineer in the IBM Event Streams team based in the UK. Through her work on IBM Event Streams she has gained experience running Apache Kafka on Kubernetes and running enterprise Kafka applications. In her previous role she specialised in cloud native Java applications and microservices architectures. Katherine has co-authored an IBM Redbook on Java microservices and has contributed to the open source microservice project Game On. She enjoys sharing her experiences and has presented at conferences around the world, including the Kafka Summit in San Francisco, Devoxx Belgium, Jfokus in Sweden and Devoxx UK.

Reacting to an Event-Driven World

Conference
Architecture

We now live in a world with data at its heart. The amount of data being produced every day is growing exponentially and a large amount of this data is in the form of events. Whether it be updates from sensors, clicks on a website or even tweets, applications are bombarded with a never-ending stream of new events. So, how can we architect our applications to be more reactive and resilient to these fluctuating loads and better manage our thirst for data? In this session explore how Kafka and Reactive application architecture can be combined in applications to better handle our modern data needs.

Reactive Manifesto
Kafka
Reactive Programming
Event Streams
Event-Driven Microservices

Running Kafka on Kube the native way with the Strimzi Operator

Conference
Cloud, Containers & Infrastructure

Apache Kafka is quickly becoming the de-facto distributed event streaming platform. It provides a scalable and reliable way to flow streams of events between your applications. But how do you keep these benefits when running it on a Kubernetes system? You need to be a domain expert on how to get Kafka and Kubernetes to work in harmony together, or find someone who is!

That's where the Strimzi operator comes in. Strimzi is an open-source Kubernetes operator that deploys and manages Kafka in a Kube-native way.

We will cover the key aspects of Kubernetes and Kafka you need to get right to deploy one onto the other and talk about how using an operator makes this easier. We will show examples of how the Strimzi operator manages Kafka effectively and set you on the right path for getting Kafka, or any other workload for that matter, deployed to Kubernetes the native way.

If you are curious about how operators can make managing applications easier, or are looking to deploy Kafka on Kubernetes this is the talk for you.

Apache Kafka
Kubernetes
Deployment Strategies