The following two applications are discussed in the first blog post:
A Flask application using the native Prometheus Python client to expose metrics via the /metrics endpoint
A Flask application which pushes the metrics to a statsd bridge which converts DogStatsd metrics to Prometheus compatible metrics.
The second blog post refers to the next application:
An aiohttp application with prometheus integeration.
This demo demonstrates how we can push HTTP metrics from a Django application into statsd exporter which is then scraped by prometheus.
This demo demonstrates howe can push statsd metrics from gunicorn running a django application. I learned about this approach from this blog post.
See blog post