For this exercise, we'll use a very simple web application available here.
git clone https://github.com/simonpasquier/simple_flask_application
cd simple_flask_application
virtualenv .
pip install -r requirements.txt
HTTP_PORT=8000 ./run.sh
Check that the application is responding on http://localhost:8000/?name=Simon.
Prometheus ships a client package to instrument Python applications. At the minimum the library can be used to get metrics about the Python process itself.
First, we need to install the package in a virtual environment:
pip install prometheus_client
Exercise: implement the /metrics handler to return Prometheus metrics.
Once done, http://localost:8080/metrics should return Prometheus metrics.
Solution
Check the client_python documentation for Flask applications.
from flask import Flask, escape, request, abort
from werkzeug.wsgi import DispatcherMiddleware
from prometheus_client import make_wsgi_app
[...]
app_dispatch = DispatcherMiddleware(app, {
'/metrics': make_wsgi_app()
})It is now fairly easy to add more application metrics to the code base.
Note that the support of metric types varies from one programming language to another. For instance, the Python client doesn't fully support summaries.
Exercise: add a counter metric tracking the number of requests received and another one tracking the number of requests that failed.
from flask import Flask, escape, request, abort
from werkzeug.wsgi import DispatcherMiddleware
from prometheus_client import make_wsgi_app, Counter
[...]
HELLO_COUNTER = Counter('hellos', 'Total number of hellos')
HELLO_FAILED_COUNTER = Counter('hellos_failed', 'Total number of failed hellos')
@app.route('/')
def hello():
HELLO_COUNTER.inc()
try:
name = request.args["name"]
return f'Hello, {escape(name)}!'
except:
HELLO_FAILED_COUNTER.inc()
abort(500)
[...]Now Prometheus should be instructed to collect metrics from the application.
Exercise: following what we've learned in the previous section, reconfigure Prometheus to scrape the /metrics endpoint.