This is data analyser microservice for YouTube course.
This application receives data from Data generator service with Apache Kafka.
Next, data is processed by Data store service.
To start an application you need to pass variables to .env
file.
You can use example .env.example
file with some predefined environments.
You can find Docker compose file in docker/docker-compose.yaml
.
Application is running on port 8082
.
All insignificant features (checkstyle, build check, dto validation) are not presented.
Just after startup application will try to connect to Apache Kafka and begin to
listen topics from KAFKA_SUBSCRIBED_TOPICS
.
You can run all course applications via docker-compose.yaml
from docker
folder.
It contains all needed configs.
NOTE: after Debezium connect is started, apply source config manually.
cd /on-startup/
sh run.sh
Note that all services must be in the same network to communicate with each other.
Debezium needs different group id than Kafka uses, so default values from .env
are 1 and 2.
Debezium is configured to push messages to data
topic due to routing in
configuration.