Streaming Design Patterns, Revolutionizing Architectures using Kafka

Building a robust, responsive, secure data service for healthcare is tricky. For starters, healthcare data lends itself to multiple models:

• Document representation for patient profile view or update

• Graph representation to query relationships between patients, providers, and medications

• Search representation for advanced lookups

Keeping these different systems up to date requires an architecture that can synchronize them in real time as data is updated. Furthermore, meeting audit requirements in Healthcare requires the ability to apply granular cross-datacenter replication policies to data and be able to provide detailed lineage information for each record. This post will describe how stream-first architectures can solve these challenges, and look at how this has been implemented at a Health Information Network provider.

This talk will go over the Kafka API with these design patterns:

• Turning the database upside down (http://martin.kleppmann.com/2015/03/04/turning-the-database-inside-out.html)

• Event Sourcing (http://martinfowler.com/eaaDev/EventSourcing.html) , Command Query Responsibity Separation (http://martinfowler.com/bliki/CQRS.html) , Polyglot Persistence (http://martinfowler.com/bliki/PolyglotPersistence.html)

• Kappa Architecture (http://milinda.pathirage.org/kappa-architecture.com/)

Speaker: Carol McDonald (https://www.mapr.com/blog/author/carol-mcdonald)