Docker lecture repository at Avito's Analytics Academy Data Science course.
To understand how the application works, install the dependencies and open these urls (using curl or a browser):
curl http://127.0.0.1:8080/books
curl http://127.0.0.1:8080/authorsThen go to this url:
http://127.0.0.1:8080/metricsHere you can see how many times you have opened /books, /authors or some other path. There is also a lot of additional information - server response time, etc.
Make a Dockerfile which uses python version 3.8 or higher as its base image, install dependencies and run server.py on port 8080. And after that build it with tag server:0.0.1.
Run the following commands:
# create network
docker network create --driver bridge webnet
# run server
docker run \
--name=server \
-d \
--rm \
-p 8080:8080 \
--network webnet \
server:0.0.1
# run prometheus
docker run \
--name=prometheus \
-v $(pwd)/prometheus.yml:/etc/prometheus/prometheus.yml \
-d \
--rm \
--network webnet \
prom/prometheus:v2.40.7
# run grafana
docker run \
--name=grafana \
-v $(pwd)/grafana/config.ini:/etc/grafana/grafana.ini \
-v $(pwd)/grafana/datasource.yml:/etc/grafana/provisioning/datasources/default.yaml \
-v $(pwd)/grafana/dashboard.yml:/etc/grafana/provisioning/dashboards/default.yaml \
-v $(pwd)/grafana/dashboards:/var/lib/grafana/dashboards \
-d \
--rm \
-p 3000:3000 \
--network webnet \
grafana/grafana:9.4.2Go to each url several times:
curl http://127.0.0.1:8080/books
curl http://127.0.0.1:8080/authorsOpen grafana in your browser.
Make a docker-compose file.
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