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 Summits in New York and London, JavaLand in Germany and JFokus in Sweden.
Any team that has made the jump from building monoliths to building microservices knows the complexities you must overcome to build a system that is functional and maintainable. Building a microservice architecture that is low latency and only communicates using REST APIs is even more tricky, with high latency for requests being a common concern. This talk will explain how you can use events as the backbone of your microservice architecture and build an efficient, event-driven system. It will cover how to get started with designing your microservice architecture and the key requirements any system needs to fulfil. It will also introduce the different patterns you will encounter in event-driven architectures and the advantages and disadvantages of these choices. Finally it will explain why Apache Kafka is a great choice for event-driven microservices.
The amount of data the world produces is growing exponentially every year and many companies are realising the potential of harnessing this data. A lot of this is generated in the form of a never ending stream of events, with publishers creating the events and subscribers consuming them in many different ways. This is where Apache Kafka comes in, Kafka isn't just a messaging system - it's an event streaming platform. This session will introduce Kafka and explain concepts such as topic partitioning, consumer groups and exactly-once semantics. Finally, learn about more advanced concepts such as stream processing using the Java Kafka Streams library, cross-datacenter replication and integration with other messaging systems.