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:

1. main idea here is: each microservice doing single simple job, but doing it well, efficient and fast

2. actor 1: twitter-data - single service which is listenning creation entity command (event) and store input data into RDBMS (Postgre SQL)

3. actor 2: scalable twitter-commander service, which is send async tweets creation commands

4. 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

5. in addition: common reusable subprojects, such domain and entity api…​

6. 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)

[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)

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

note:

1. <-> - sync processing

2. <~> - async processing

quick start

gradle --parallel bootRun

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

http get :8882

gradle --stop

stack:

1. spring-boot

2. spring-data

3. spring-cloud-stream

4. RabbitMQ

5. Postgres

6. docker (docker-compose)

7. gradle

8. install spring app as linux service

9. CQRS and Event Sourcing

10. event-driven architecture

11. reactive streams, non-blocking data processing