What are the key factors to consider when developing event-driven architecture? In this podcast, Adam Bellemare, Staff Technologist at Confluent, discusses the 4 dimensions of events and designing event streams along with best practices, and an overview of a new course he just authored. This course, called Introduction to Designing Events and Event Streams, walks you through the process of properly designing events and event streams in any event-driven architecture.
Is real-time data streaming the future, or will batch processing always be with us? In this episode, Kris talks to a panel of industry experts with decades of experience building and implementing data systems. They discuss the state of streaming adoption today, if streaming will ever fully replace batch, and whether it even could (or should).
Is it possible to build a real-time data platform without using stateful stream processing? Forecasty.ai is an artificial intelligence platform for forecasting commodity prices, imparting insights into the future valuations of raw materials for users. Nearly all AI models are batch-trained once, but precious commodities are linked to ever-fluctuating global financial markets, which require real-time insights. In this episode, Ralph Debusmann (CTO, Forecasty.ai) shares their journey of migrating from a batch machine learning platform to a real-time event streaming system with Apache Kafka and delves into their approach to making the transition frictionless.
How do you set data applications in motion by running stateful business logic on streaming data? Capturing key stream processing events and cumulative statistics that necessitate real-time data assessment, migration, and visualization remains as a gap—for event-driven systems and stream processing frameworks according to Fred Patton (Developer Evangelist, Swim Inc.) In this episode, Fred explains streaming applications and how it contrasts with stream processing applications. Fred and Kris also discuss how you can use Apache Kafka and Swim for a real-time UI for streaming data.
How do you build an event-driven application that can react to real-time data streams as they happen? Kris Jenkins (Senior Developer Advocate, Confluent) will be hosting another fun, hands-on programming workshop—Coding in Motion: Watching the River Flow, to demonstrate how you can build a reactive event streaming application with Apache Kafka, ksqlDB using Python.
If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.
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