Reactive Architectures
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The document discusses reactive architectures and their application in modern software development, focusing on scalability, resilience, and responsiveness. It emphasizes the integration of functional reactive programming, asynchronous communication, and various communication protocols like HTTP and WebSockets to enhance user experience and service interaction. Key elements include leveraging microservices, polyglot persistence, event sourcing, and deployment strategies to enable efficient and high-performing systems.
Reactive Architectures
- 1. Reactive Architectures Ralph Winzinger, Senacor Technologies
- 2. who am I? Ralph Winzinger Principal Architect, Senacor Technolgies emerging technolgies, high scalable architectures, engineering processes, dissemination of knowledge @rwinz ralph.winzinger@senacor.com
- 3. what’s up? why reactive? application structure deployment & operating organizational impact development process functional reactive programming
- 4. aspirin - candy for programmers https://www.flickr.com/photos/atul666/237027107
- 5. what’s up? why reactive? application structure deployment & operating organizational impact development process functional reactive programming
- 8. architectural blueprint HTML / JS service legacy / core integration IoT 3rd… API gateway service IMDG native, reactive user experience, optimized for low bandwidth access offer high scalable service integration to address fine grained request/response cycles and various 3rd parties maximize functional decoupling and vertical decomposition up to microservices optimized persistence technology aligned with functional requirement up to high performance in-memory computing transparently integrate legacy systems into state-of-the-art architectures …
- 9. clients & integration high quality, native like user experience mobile first, responsive design (if not native) async communication for maximized responsiveness full-duplex communication (push, partial update) high scalable gateway services, optimized for handling finegrained requests, long polling requests, server push integration of new channels (e.g. WebRTC, messaging, voice, video-chat) async, non-blocking Angular.js Node.js / Vert.x
- 10. services no app containers shared nothing service architecture for easy scale out independent development and deployment vertical decomposition aligned with functional features further breakdown towards single responsibility ans micro services lightweight communication, self discovery at best resilient inter-service connection for failover and scalability spring boot vert.x
- 11. shared nothing, almost service service service maximum isolation between services - no shared state (including persistence) - no shared domain model or logic easy scale out & easy failover share non-functional infrastructure code - network access, serialization, failover, … Asgard, Hystrix, Ribbon, Finagle, Simian Army, Hazelcast, …
- 12. λ I’ve seen the light … ! lambdas streams optionals futures https://github.com/ReactiveX/RxJava RxJava observable observable future loads of functions
- 13. persistence primary goal: efficiency oracle mongo neo4jhadoop ???
- 14. persistence primary goal: efficiency polyglot persistence - the best tool for the job IMDG - high performance cache first approach
- 16. „How did we end up here?“, Trisha Gee & Todd Montgomery, QCon NY 2015
- 18. event sourcing derive object state := left fold all events every state change is triggered by an event apply(apply(apply(apply(new, ev0), ev1), ev2), …) do not store state, but events so … no persistent state … but how do I query data?
- 19. event sourcing & CQRS aggregate createEvent(cmd) apply(ev) command publish consumestore social service consume hadoop graphDB analytics service query
- 20. serialization service service human readable data formats are great! yeah! except there is no human to read that stuff … 😣
- 21. serialization java ser XMLJSONcapnproto protobuf size speed java ser XMLJSONcapnproto protobufjava ser XMLJSONcapnproto protobuf
- 22. serialization java ser XMLJSONcapnproto protobuf size speed java ser XMLJSONcapnproto protobufjava ser XML JSON capnproto protobuf
- 23. serialization java ser XMLJSONcapnproto protobuf size speed java ser XMLJSONcapnproto protobufjava ser XML JSON capnproto protobuf
- 24. serialization java ser XMLJSONcapnproto protobuf size speed java ser XMLJSONcapnproto protobufjava ser XML JSON capnproto protobuf
- 25. serialization java ser XMLJSONcapnproto protobuf size speed java ser XMLJSONcapnproto protobuf java ser XML JSON capnproto protobuf
- 26. serialization java ser XMLJSONcapnproto protobuf size speed java ser XML JSON capnproto protobuf java ser XML JSON capnproto protobuf
- 27. deployment & ops scale out & resilience one service per server ultra-fast deployment precise monitoring
- 28. wanna play? message based communication auto discovery location agnostic deployment service monitoring auto spawning / suicide setup / tear down virtual machines async / parallel service calls local caching fallback services service call timeout partial page update server -> client push circuit breaker back pressure / thrott bulk head
- 29. wanna play? angular.js + websockets vert.x 3 + Java8 + RxJava hystrix + dashboard mongoDB 1000-2000 tps @rwinz ralph.winzinger@senacor.com