Homework

Docker lecture repository at Avito's Analytics Academy Data Science course.

Step 1:

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/authors

Then go to this url:

http://127.0.0.1:8080/metrics

Here 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.

Step 2.

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.

Step 3.

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:9.4.2

Step 4.

Go to each url several times:

curl http://127.0.0.1:8080/books
curl http://127.0.0.1:8080/authors

Step 5.

Open grafana in your browser.

Step 6.

Make a docker-compose file.