Swagger generated server

Overview

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.

Requirements

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

Configuration

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.

Usage

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

Running with Docker

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