This server was generated by the swagger-codegen project. By using the OpenAPI-Spec from a remote server, you can easily generate a server stub. This is an example of building a swagger-enabled Flask server.
This example uses the Connexion library on top of Flask.
Python 3.5.2+
Kubernetes API
The Kubernetes v1 API is required to extract compute metrics of the cluster.
Heketi API
The Heketi API is required to extract the usage metrics of GlusterFS volumes. As Kubernetes does not provide a native solution for that, such APIs are needed on top of the Kubernetes cluster. The endpoint format configured is:
hostname/api/v1/namespaces/kube-system/services/heketi:8080/proxy/metrics
The needed configuration files are:
/etc/ditas/vdc/data-analytics.json
and
/opt/blueprint/blueprint.json
The Data Analytics gets information about all infrastructure Kubernetes masters from the COOKBOOK_APPENDIX, it then matches the information provided in the GET request (infraId) with the available infrastructure names. The endpoints are expected to be available on port 9999.
The data-analytics.json file is expected to contain information about the ElasticSearch endpoint:
{
"Port":8080,
"ElasticSearchURL":"{{.elasticsearch_url}}"
}
The index name is compiled in the format:
'{}-*'.format(infraId)Where infraId is a query paramter to the metrics GET call.
To run the server, please execute the following from the root directory:
pip3 install -r requirements.txt
python3 -m swagger_server
and open your browser to here:
http://hostname:8080/data-analytics/ui/
Your Swagger definition lives here:
http://hostname:8080/data-analytics/swagger.json
To launch the integration tests, use tox:
sudo pip install tox
tox
To run the server on a Docker container, please execute the following from the root directory:
# building the image
docker build -t swagger_server .
# starting up a container
docker run -p 8080:8080 swagger_server