Easily Leveraging Messaging Platforms such as Kafka for Real-time Streaming Transaction Processing
Unfortunately, most of us suffer from the complexity of the architectures required for real-time data processing at scale. Many technologies need to be stitched together, and each technology is often complex by itself. Usually, we end up with a strong discrepancy between how we, as engineers, would like to work vs. how we end up working in practice.
In this session, we will talk about how to radically simplify the architecture and speed up development time and application latency. We will cover how you can build applications to serve real-time processing needs without having to spend months building infrastructure, while still benefiting from properties such as guaranteed delivery, high scalability, distributed computing, and fault-tolerance. We will discuss use cases where stream processing often requires transactional and database-like functionality. Kafka (or any messaging broker) allows you to bridge the worlds of streams and databases when implementing core business applications (inventory management for large retailers, IoT based patient sensor monitoring in healthcare, fleet tracking in logistics, etc.), for example in the form of event-driven, containerized microservices.
Join us Thursday, October 19th with Colin McNaughton, Head of Engineering at Neeve Research, and an author on several open source projects including Eagle, Robin, and Lumino. Colin will share experience, techniques, and best practices for building real-time applications and services using X Platform™, a powerful, easy-to-use library for developing highly scalable, fault-tolerant, distributed stream processing applications on top of Apache Kafka or other messaging brokers.