Drinking from the Stream: How to use messaging platforms for scalability & performance

Maintainer

• Mark Heckler

• [email protected]

• @mkheck on Twitter

Purpose

This multi-repo accompanies my session titled "Drinking from the Stream: How to use messaging platforms for scalability & performance" and includes all code written within the session and potentially more…​star+watch this repo for updates!

Related repository

Scripts I use to create, configure, & run RabbitMQ & Apache Kafka locally in support of this session

Related presentation

"Drinking from the Stream: How to use messaging platforms for scalability & performance" presentation

Build and Run

Build

You can build .jar files like so:

mvn clean package -f scst-source/pom.xml
mvn clean package -f scst-processor/pom.xml
mvn clean package -f scst-sink/pom.xml

Run

Due to dependencies on Kafka and RabbitMQ it is recommended that you use docker-compose to run the apps:

docker-compose up -d

It will take a few minutes to start and then you can view the docker logs to see the coffee get processed:

docker-compose logs -f source processor sink

You should see output that looks like this:

source_1     | WholesaleCoffee(id=74cceff9-97bd-45aa-8458-76cc00b770c1, name=Kaldi's)
processor_1  | RetailCoffee(id=74cceff9-97bd-45aa-8458-76cc00b770c1, name=Kaldi's, state=WHOLE_BEAN)
sink_1       | RetailCoffee(id=74cceff9-97bd-45aa-8458-76cc00b770c1, name=Kaldi's, state=WHOLE_BEAN)
source_1     | WholesaleCoffee(id=5494c658-f673-4008-8aa0-5cdc77e3ec8a, name=Cereza)
processor_1  | RetailCoffee(id=5494c658-f673-4008-8aa0-5cdc77e3ec8a, name=Cereza, state=WHOLE_BEAN)
sink_1       | RetailCoffee(id=5494c658-f673-4008-8aa0-5cdc77e3ec8a, name=Cereza, state=WHOLE_BEAN)
source_1     | WholesaleCoffee(id=f8850d88-b1ae-40db-b625-3ebb878571a1, name=Sumatra)
processor_1  | RetailCoffee(id=f8850d88-b1ae-40db-b625-3ebb878571a1, name=Sumatra, state=WHOLE_BEAN)
sink_1       | RetailCoffee(id=f8850d88-b1ae-40db-b625-3ebb878571a1, name=Sumatra, state=WHOLE_BEAN)