FastStream simplifies event stream development. Learn its origin, basics, and advanced features in our talk. This year, we dive into technical nuances to inspire developers and boost open source contributions.
Here to make your journey through the intricate world of microservices and data streaming a whole lot smoother, FastStream was developed out of the need to seamlessly handle machine learning models in Kafka setups. Acting as a unifying tool, this Python library simplifies the complexities of building, testing, and deploying microservices, especially when it comes to efficient data streaming.
In the first part of our talk, we’ll start by introducing FastStream and how it came to be. We’ll explore why we created it and the history that led to its development. After that, we’ll move on to the basics of FastStream. We’ll walk you through the simple steps of creating services, connecting to message systems, and effectively handling messages. This basic knowledge is crucial as it is the foundation for diving deeper into FastStream’s advanced features and applications, which we’ll cover in the later part of our talk.
In the past year, our talks were focused on spreading the word about FastStream and raising awareness about its capabilities. This year, we’re shifting gears toward more technical talks. In the second half of the talk, we’ll focus on the technical nuances of FastStream—implementation details and the development environment. Hopefully, this will inspire other developers not only to adopt FastStream, but also to improve their open source contribution environments.
We developed FastStream out of the necessity for an elegant solution to serve our ML models in a Kafka environment. It was mainly created for us, by us and this is why I am confident that this talk will be ideal for people that would describe themselves with the same words as we would ourselves: microservice developers, library enthusiasts, and data/AI scientists interested in optimizing their microservices with efficient data streaming using FastStream.
I am currently working as a Python developer at airt. In the past three years, I have gained valuable experience in the industry, including a year working on a microservice product that uses Apache Kafka for communication between services.
I am a strong believer in the power of open source software, and I enjoy learning from the open source community. My interests in the field at the moment include machine learning, model deployment, Apache Kafka, and advanced Python programming.