Reactivity is defined as programming with asynchronous data streams, which are data containers that exist in plural space and asynchronous time.
Reactive programming makes the relationship between variables explicit using streams, shifting from a pull-based design to a push-based design for automatic updates.
The Reactive Manifesto guides building responsive systems by achieving elasticity and resilience through a message-driven architecture that supports back pressure and location transparency.
Microservice architectures evolved from synchronous pull-based models to fully asynchronous, stream-centric systems using event sourcing and functions-as-a-service.
GraphQL subscriptions provide the missing piece for end-to-end reactivity by enabling push-based data streaming from the server to the client.
A reactive architecture enables real-time synchronization between an insurance agent's and a customer's UI, allowing for seamless collaboration.
Projections, or specialized read models hydrated from an event store, allow read-heavy features like viewing balances to remain available even when backend services fail.
While reactive architectures offer powerful options like resilience and real-time capabilities, they introduce significant complexity and should be adopted judiciously.
46:24David Leitner
39:10Niklas Heidloff
59:03Florian Rappl
34:28Uri Goldshtein
28:12Gregor Bauer
47:48William Lyon
40:45Josh Goldberg
25:41Jan Weinschenker
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Jobs that call for the skills explored in this talk.
Peter Park System GmbH
München, Germany
Schulz.codes GmbH
Darmstadt, Germany
doinstruct Software GmbH
Berlin, Germany
Nia Health GmbH
Berlin, Germany
Haufe-Lexware GmbH & Co. KG
Freiburg im Breisgau, Germany
CONTIAMO GMBH
Berlin, Germany
