grafana django dashboard ¶

django-prometheus ¶

Export Django monitoring metrics for Prometheus.io

Usage ¶

Requirements ¶

Django >= 1.8

Installation ¶

Install with:

pip install django-prometheus

Or, if you’re using a development version cloned from this repository:

python path-to-where-you-cloned-django-prometheus/setup.py install

This will install prometheus_client as a dependency.

Quickstart ¶

In your settings.py:

             INSTALLED_APPS = (
   ...
   'django_prometheus',
   ...
)

MIDDLEWARE_CLASSES = (
    '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 your urls.py:

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

            

Monitoring your databases ¶

SQLite, MySQL, and PostgreSQL databases can be monitored. Just replace the ENGINE property of your database, replacing django.db.backends with django_prometheus.db.backends .

             DATABASES = {
    'default': {
        'ENGINE': 'django_prometheus.db.backends.sqlite3',
        'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
    },
}

            

Monitoring your caches ¶

Filebased, memcached, redis caches can be monitored. Just replace the cache backend to use the one provided by django_prometheus django.core.cache.backends with django_prometheus.cache.backends .

             CACHES = {
    'default': {
        'BACKEND': 'django_prometheus.cache.backends.filebased.FileBasedCache',
        'LOCATION': '/var/tmp/django_cache',
    }
}

            

Monitoring your models ¶

You may want to monitor the creation/deletion/update rate for your model. This can be done by adding a mixin to them. This is safe to do on existing models (it does not require a migration).

If your model is:

             class Dog(models.Model):
    name = models.CharField(max_length=100, unique=True)
    breed = models.CharField(max_length=100, blank=True, null=True)
    age = models.PositiveIntegerField(blank=True, null=True)

            

Just add the ExportModelOperationsMixin as such:

             from django_prometheus.models import ExportModelOperationsMixin

class Dog(ExportModelOperationsMixin('dog'), models.Model):
    name = models.CharField(max_length=100, unique=True)
    breed = models.CharField(max_length=100, blank=True, null=True)
    age = models.PositiveIntegerField(blank=True, null=True)

            

This will export 3 metrics, django_model_inserts_total{model="dog"} , django_model_updates_total{model="dog"} and django_model_deletes_total{model="dog"} .

Note that the exported metrics are counters of creations, modifications and deletions done in the current process. They are not gauges of the number of objects in the model.

Starting with Django 1.7, migrations are also monitored. Two gauges are exported, django_migrations_applied_by_connection and django_migrations_unapplied_by_connection . You may want to alert if there are unapplied migrations.

If you want to disable the Django migration metrics, set the PROMETHEUS_EXPORT_MIGRATIONS setting to False.

Monitoring and aggregating the metrics ¶

Prometheus is quite easy to set up. An example prometheus.conf to scrape 127.0.0.1:8001 can be found in examples/prometheus .

Here’s an example of a PromDash displaying some of the metrics collected by django-prometheus:

Adding your own metrics ¶

You can add application-level metrics in your code by using prometheus_client directly. The exporter is global and will pick up your metrics.

To add metrics to the Django internals, the easiest way is to extend django-prometheus’ classes. Please consider contributing your metrics, pull requests are welcome. Make sure to read the Prometheus best practices on instrumentation and naming .

Importing Django Prometheus using only local settings ¶

If you wish to use Django Prometheus but are not able to change the code base, it’s possible to have all the default metrics by modifying only the settings.

First step is to inject prometheus’ middlewares and to add django_prometheus in INSTALLED_APPS

            MIDDLEWARE = (
        ('django_prometheus.middleware.PrometheusBeforeMiddleware',) +
       MIDDLEWARE +
        ('django_prometheus.middleware.PrometheusAfterMiddleware',)
    )

INSTALLED_APPS = INSTALLED_APPS + ('django_prometheus',)

           

Second step is to create the /metrics end point, for that we need another file (called urls_prometheus_wrapper.py in this example) that will wraps the apps URLs and add one on top:

            from django.conf.urls import include, url

urlpatterns = []

urlpatterns.append(url('^prometheus/', include('django_prometheus.urls')))
urlpatterns.append(url('', include('myapp.urls')))

This file will add a “/prometheus/metrics” end point to the URLs of django that will export the metrics (replace myapp by your project name).

Then we inject the wrapper in settings:

            ROOT_URLCONF = "graphite.urls_prometheus_wrapper"

           