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When a user of a social network updates her profile, that profile update needs to propagate to several databases that want to know about such an update–search indexes, user databases, caches, and other services. When Neha Narkhede was at LinkedIn, she helped develop Kafka, which was deployed at LinkedIn to help solve this very problem. Using Kafka as an event queue, LinkedIn adopted the CQRS architectural pattern together with event sourcing.
Event sourcing is an architectural pattern that allows changes to our application model to be represented as events. Each event is published to an event queue, and is pulled off of the queue by each of the various services that need to consume that event. Event sourcing and the related architectural pattern CQRS allow for a flow of information through an application that is easy to reason about, and has several other desirable properties.
In today’s episode, Neha explains how to use Kafka for event sourcing and how related software patterns are improving the architectures of companies like Netflix and Uber.
For more information, check out this Confluent blog entry.