► LEARN MORE: https://cnfl.io/microservices-101-module-1

In this video, we'll look at some techniques for evolving events by analyzing a specific use case in a banking fraud detection system.

Check out the Designing Event-Driven Microservices course on Confluent Developer for more details: https://cnfl.io/microservices-101-module-1

It's rare in modern software to build a system that is static, and unchanging. Most systems are impacted by fluctuations in the business environment. Teams are forced to evolve their event schemas to adapt to new requirements. However, these evolutions must be performed in a live system, without incurring downtime. That requires careful planning to ensure that both the producer and consumer of the data streams can be updated independently to avoid having to synchronize deployment.

RELATED RESOURCES
► Schema Evolution Explained - https://youtu.be/XG-EVX6PEFo
► Event-Driven Microservices in Banking and Fraud Detection - https://youtu.be/tFTvFHDnkb4
► Defining Asynchronous Microservice APIs for Fraud Detection - https://youtu.be/GNDOMJAT3T0
► Extracting a Fraud Detection Microservice from a Bank System - https://youtu.be/8q-Eb0rokX4
► Using Asynchronous Events to enrich Fraud Detection - https://youtu.be/rg--K26xrvQ
► Microservice Pitfalls: Solving the Dual-Write Problem - https://youtu.be/4GffyiSZri4
► Microservices course playlist - https://bit.ly/designing-event-driven-microservices-playlist

CHAPTERS

00:00 - Intro

00:55 - Digital Fingerprints in Fraud Detection.

01:33 - Evolving Message Schemas with Additive Changes.

02:26 - Consumer First Approaches to Evolving a Schema.

03:12 - Producer First Approaches to Evolving a Schema.

03:53 - Replaying Old Events.

04:41 - Evolving Existing Fields in a Schema.

05:54 - Versioning, and Replacing Events

06:51 - Closing

ABOUT CONFLUENT
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