For their inaugural episode, Anna McDonald (the Duchess), Matthias J. Sax (the Doctor), and their extinct friend, Phil, wax rhapsodic about all things eventing: you’ll learn why events are a mindset, why the Duchess thinks you’ll find event immutability relaxing, and why your event streams might need some windows. The Duchess & The Doctor Show features a question-driven format that delivers substantial, yet easily comprehensible answers to user-submitted questions on all things events and eventing, including Apache Kafka, its ecosystem, and beyond!

Learn how Apache Flink® can handle hundreds or even thousands of compute nodes running 24/7 and still produce correct results.

Learn how consumer partition assignment works in Apache Kafka.

In this video, Adam Bellemare compares and contrasts Event-Driven and Request-Driven Architectures to give you a better idea of the tradeoffs and benefits involved with each. Many developers start in the synchronous request-response (RR) world, using REST and RPC to build inter-service communications. But tight service-to-service coupling, scalability, fan-out sensitivity, and data access issues can still remain.

Every company faces the perennial problem of data integration but often experiences data silos, data quality issues, and data loss from point-to-point, batch-based integrations. Connectors decouple data sources and sinks through Apache Kafka, simplifying your architecture while providing flexibility, resiliency, and reliability at a massive scale.

An Event-Driven Architecture is more than just a set of microservices. Event Streams should represent the central nervous system, providing the bulk of communication between all components in the platform. Unfortunately, many projects stall long before they reach this point.

Tired of starting online tutorials only to realize they don't work on your machine? We've integrated Gitpod into our Confluent Developer courses to streamline your learning experience. See how it works in this short introduction video.

Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations.

Join the Confluent leadership team as they share their vision of streaming data products enabled by a data streaming platform built around Apache Kafka. Jay Kreps, Co-creator of Apache Kafka and CEO of Confluent, will present his vision of unifying the operational and analytical worlds with data streams and showcase exciting new product capabilities. During this keynote, the winner and finalists of the $1M Data Streaming Startup Challenge will showcase how their use of data streaming is disrupting their categories.

Stream processing plays a critical role in the infrastructure stack for data streaming. Developers can use it to filter, join, aggregate, and transform their data streams on the fly to power real-time applications and streaming data pipelines. Among stream processing frameworks, Apache Flink has emerged as the de facto standard because of its performance and rich feature set. However, self-managing Flink (like self-managing other open source tools like Kafka) can be challenging due to its operational complexity, steep learning curve, and high costs for in-house support.