Designing an Asynchronous Microservices Runtime with Kafka: State, Scale and Performance
Today's world operates under a new set of constraints and tries to solve problems that were never thought possible. Everything has changed.
This talk will cover the origins of how Apache Kafka came to be along with how it now underpins some of the worlds largest microservice ecosystems. Kafka and the microservice movement gathered momentum at the same time, Kafka for streams or data-in-motion and microservices as a new, fine-grained architectural principle. The thorn in the side for microservices has always been about the ability to handle, state, and scale. Kafka, meanwhile has always been good at distributing state, which means, that now as we build microservices on top of Kafka, there is a natural affinity between them. I will cover the evolution of microservices until the point of today and then work through how we can build stateful scalable microservices using Kafka. You will learn how scaling state works, and also how it can be queried with ‘interactive queries’.
- Scalable business processing
- Run it on rails: Instrumentation and monitoring
- Control flow patterns (start, stop, pause)
- Error handling strategies
Experiments in Teaching a Machine to Code
I've set myself a goal. Can I get a machine learning algorithm to generate code that can pass a unit test? This talk will track the experiments I run as I try to achieve this.
In this talk, we'll explore:
- How to take an experiment based approach to machine learning development
- How to start small and iterate
- How transfer learning works for natural language processing and
- Get an overview of the LSTM architecture