= spring-boot-twitter image:https://travis-ci.org/daggerok/spring-boot-twitter.svg?branch=master["Build Status", link="https://travis-ci.org/daggerok/spring-boot-twitter"]

== added all backing- and micro- services into sinle docker-compose

see: ./twitter-docker/twitter-docker-services/src/docker-compose.yml

this repo demonstrate CQRS data transfer in REST API and messaging microservices. it's containing (async RabbitMQ messaging and sync REST microservices) data models processing:

. main idea here is: each microservice doing single simple job, but doing it well, efficient and fast . actor 1: twitter-data - single service which is listenning creation entity command (event) and store input data into RDBMS (Postgre SQL) . actor 2: scalable twitter-commander service, which is send async tweets creation commands . actor 3: scalable twitter-query service, which is only reading tweets from read-only datasorce. in production systems should be moved out from operational RDBMS to some nosql scalable / replicateble solution, such mongodb, or any other more siutable for you . in addition: common reusable subprojects, such domain and entity api... . important keywords:

• CQRS, event sourcing
• reactive streams, event-driven architecture
• messaging pipelines, non-blocking data processing

== reads (can be improoved by spring 5 reactive programming model using Mono / Flux)

[source]

[client] <-> (http get) <-> [twitter-query] <-> (jdbc select) <-> [rdbms]

with webflux and reactive data-source could also be non blocking:

[client] <~> (http get sse) <~> [twitter-query (webflux)] <~> (reactive flux) <~> [mongo]

== writes (also can be improved by replacing rdbms solution with some siutable reactive nosql)

[source]

[client] -> (http post) -> [twitter-command] ~> (send async) ~> [twitter-data] <-> (jdbc insert) <-> [rdbms]

note:

. \<\-> - sync processing . <~> - async processing

== quick start

[source,bash]

gradle --parallel bootRun

http post :8881 data=test-tweet1 http post :8881 data=test-tweet2

http get :8882

gradle --stop

== stack:

. spring-boot . spring-data . spring-cloud-stream . RabbitMQ . Postgres . docker (docker-compose) . gradle . install spring app as linux service . CQRS and Event Sourcing . event-driven architecture . reactive streams, non-blocking data processing