Building and Designing Events and Event Streams with Apache Kafka

Streaming Audio: Apache Kafka® & Real-Time Data

What are the key factors to consider when developing event-driven architecture? When properly designed, events can connect existing systems with a common language and allow data exchange in near real time. They also help reduce complexity by providing a single source of truth that eliminates the need to synchronize data between different services or applications. They enable dynamic behavior, allowing each service or application to respond quickly to changes in its environment. Using events, developers can create systems that are more reliable, responsive, and easier to maintain.
In this podcast, Adam Bellemare, staff technologist at Confluent, discusses the four 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.
Adam explains that the goal of the course is to provide you with a foundation for designing events and event streams. Along with hands-on exercises and best practices, the course explores the four dimensions of events and event stream design and applies them to real-world problems. Most importantly, he talks to Kris about the key factors to consider when deciding what events to write, what events to publish, and how to structure and design them to trigger actions like broadcasting messages to other services or storing results in a database.
How you design and implement events and event streams significantly affect not only what you can do today, but how you scale in the future. Head over to Introduction to Designing Events and Event Streams to learn everything you need to know about building an event-driven architecture.
EPISODE LINKS

• Introduction to Designing Events and Event Streams
• Practical Data Mesh: Building Decentralized Data Architecture with Event Streams
• The Data Dichotomy: Rethinking the Way We Treat Data and Services
• Coding in Motion: Sound & Vision—Build a Data Streaming App with JavaScript and Confluent Cloud
• Using Event-Driven Design with Apache Kafka Streaming Applications ft. Bobby Calderwood
• Watch the video version of this podcast
• Kris Jenkins’ Twitter
• Streaming Audio Playlist
• Join the Confluent Community
• Learn more with Kafka tutorials, resources, and guides at Confluent Developer
• Live demo: Intro to Event-Driven Microservices with Confluent
• Use PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)

章

1. Intro (00:00:00)

2. Overview of new training course (00:01:44)

3. Internal vs. external events (00:04:34)

4. Fact vs. delta (00:10:13)

5. Denormalization vs. normalization (00:22:38)

6. Single event type vs. multiple event types per topic (00:33:23)

7. Use-case: same event type on multiple different topics (00:40:04)

8. Discreet vs. continuous (00:42:49)

9. It's a wrap! (00:51:14)