This project stores machine parameters and calculates different metrics of them (average, median, min, max) within a time limit.
The project has been developed using spring cloud function. Data is stored in mongodb. All deployment has been managed by docker-compose.
- java 11
- maven
- docker
mvn clean package
docker-compose up --build
Endpoint to insert machine parameters into the datastore
curl -i -X POST -H "Content-Type: application/json" http://localhost/machines -d '{ "machineKey": "embosser", "parameters": {"core_diameter": 3, "speed": 20 }}'
# Insert parameters mentioned in the `parameters.csv` file
curl -i -X POST -H "Content-Type: application/json" http://localhost/machines -d '{ "machineKey": "ajoparametrit", "parameters": {"TS_setpoint_tail_length": 15, "perforation_length": 16.5, "core_interference": 15, "number_of_sheets": 17.7 }}'
curl -i -X POST -H "Content-Type: application/json" http://localhost/machines -d '{ "machineKey": "aufwickler", "parameters": {"log_diameter": 15, "speed": 35.6 }}'
curl -i -X POST -H "Content-Type: application/json" http://localhost/machines -d '{ "machineKey": "wickelkopf", "parameters": {"core_interference": 25.7, "speed": 27.5 }}'
Endpoint to get latest parameters
curl -i -X GET -H "Content-Type: application/json" http://localhost/machine-latest-parameters
Endpoint to get metrics of a machine
curl -i -X POST -H "Content-Type: application/json" http://localhost/machine-metrics -d '{ "machineKey": "embosser", "minutesFrom": 100 }'
- Docker script can be found in
Dockerfile - Docker compose environments can be found in
.env
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