How to monitor a Django application with Prometheus

Introduction

Prometheus is an open-source systems monitoring and alerting toolkit that can be used to easily and cheaply monitor infrastructure and applications. In this tutorial we show how to monitor a Django application with Prometheus. (And even if you don’t have a Django application, we include an optional step to create one so that everyone can follow along.)

Prerequisites

A machine with the following installed:

• Python
• pip
• A locally running Prometheus instance

tip

Since machines commonly have multiple versions of Python installed, in this tutorial we call pip using the python -m pip [foo] syntax instead of the pip [foo] syntax. This is to ensure that pip installs new components for the version of Python that we are using.

Step 1 - Set up a basic Django application (optional)

(Please skip this step if you already have a Django application.)

Install Django

python -m pip install Django

More info on Django.

Create a template project

Navigate to the directory where you want to create the project, and run:

django-admin startproject mysite

This creates a mysite directory in your current directory, that looks something like this (more here):

mysite/
    manage.py
    mysite/
        __init__.py
        settings.py
        urls.py
        asgi.py
        wsgi.py

Verify that Django is working

Change to the outer mysite directory, and run:

python manage.py runserver

You should see something like this:

Performing system checks...
System check identified no issues (0 silenced).
You have unapplied migrations; your app may not work properly until they are applied.
Run 'python manage.py migrate' to apply them.
March 10, 2020 - 15:50:53
Django version 3.0, using settings 'mysite.settings'
Starting development server at http://127.0.0.1:8000/
Quit the server with CONTROL-C.

If that works, then visit http://127.0.0.1:8000/ from your Web browser. You should see a “Congratulations!” page, with a rocket taking off.

(If that didn’t work, then please take a look at the Django documentation for troubleshooting.)

Step 2 - Export prometheus-style monitoring metrics from your Django application

We use the django-prometheus package for exporting prometheus-style monitoring metrics from our Django application.

Install django-prometheus

python -m pip install django-prometheus

Modify settings.py and urls.py

In settings.py, add:

INSTALLED_APPS = [
   ...
   'django_prometheus',
   ...
]
MIDDLEWARE = [
    'django_prometheus.middleware.PrometheusBeforeMiddleware',
    # All your other middlewares go here, including the default
    # middlewares like SessionMiddleware, CommonMiddleware,
    # CsrfViewmiddleware, SecurityMiddleware, etc.
    'django_prometheus.middleware.PrometheusAfterMiddleware',
]

In urls.py, make sure you have this in the header:

from django.conf.urls import include, path

Then add this under urlpatterns:

urlpatterns = [
    ...
    path('', include('django_prometheus.urls')),
]

Verify that metrics are being exported

Restart the application and curl the /metrics endpoint:

python manage.py runserver
curl localhost:8000/metrics

(Alternatively, once you’ve restarted your application, visit http://localhost:8000/metrics from your web browser.)

You should see something like this:

# HELP python_gc_objects_collected_total Objects collected during gc
# TYPE python_gc_objects_collected_total counter
python_gc_objects_collected_total{generation="0"} 11716.0
python_gc_objects_collected_total{generation="1"} 1699.0
python_gc_objects_collected_total{generation="2"} 616.0
# HELP python_gc_objects_uncollectable_total Uncollectable object found during GC
# TYPE python_gc_objects_uncollectable_total counter
python_gc_objects_uncollectable_total{generation="0"} 0.0
python_gc_objects_uncollectable_total{generation="1"} 0.0
python_gc_objects_uncollectable_total{generation="2"} 0.0
# HELP python_gc_collections_total Number of times this generation was collected
# TYPE python_gc_collections_total counter
python_gc_collections_total{generation="0"} 7020.0
python_gc_collections_total{generation="1"} 638.0
python_gc_collections_total{generation="2"} 34.0
# HELP python_info Python platform information
# TYPE python_info gauge
python_info{implementation="CPython",major="3",minor="8",patchlevel="0",version="3.8.0"} 1.0
...

Step 3 - Point Prometheus to your Django application metrics endpoint

(Note: This section assumes that you have a locally running Prometheus instance.)

Update prometheus.yml

Under scrape_configs:, add:

- job_name: django
  scrape_interval: 10s
  static_configs:
  - targets:
    - localhost:8000

note

Replace the job_name, django, with your preferred prefix for Django application metrics in Prometheus. For example, you can use webapp.

Restart Prometheus

./prometheus --config.file=prometheus.yml

Verify that Prometheus is scraping metrics from your Django application:

Once you are running Prometheus locally, visit the Prometheus Expression Browser (running on localhost) from your web browser.

For example, you can visit the below page, which graphs the total number of http requests your Django application received in the last hour:

Graph of Django HTTP requests, served on localhost

It should look something like this:

If you’d like to do more testing, visit your Django application several more times and reload the Prometheus Expression Browser to confirm that it is working. Also feel free to explore the other Django metrics that Prometheus is collecting.

Step 4 - Instrument additional aspects of your application (optional)

Django-prometheus is quite powerful, and allows you to easily instrument additional aspects of your application, including:

• Your databases
• Your models (for example, monitor the creation/deletion/update rate for your models)
• Your caches
• Your own custom metrics in your code

More information on how to do all of these is here.

Next steps

Congratulations! Now you are monitoring your Django application with Prometheus!

Looking for something to do next? You can start building dashboards to monitor key metrics in real-time, using another open-source tool for your visualizations, like Grafana.