Package: django-prometheus
django-prometheusExport Django monitoring metrics for Prometheus.ioFeaturesThis library provides Prometheus metrics for Django related operations:Requests & ResponsesDatabase access done viaDjango ORMCache access done viaDjango Cache frameworkUsageRequirementsDjango >= 3.2Python 3.7 and above.InstallationInstall with:pipinstalldjango-prometheusOr, if you're using a development version cloned from this repository:pythonpath-to-where-you-cloned-django-prometheus/setup.pyinstallThis will installprometheus_clientas a dependency.QuickstartIn your settings.py: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 your urls.py:urlpatterns=[...path('',include('django_prometheus.urls')),]ConfigurationPrometheus uses Histogram based grouping for monitoring latencies. The default
buckets are:PROMETHEUS_LATENCY_BUCKETS=(0.01,0.025,0.05,0.075,0.1,0.25,0.5,0.75,1.0,2.5,5.0,7.5,10.0,25.0,50.0,75.0,float("inf"),)You can define custom buckets for latency, adding more buckets decreases performance but
increases accuracy:https://prometheus.io/docs/practices/histograms/PROMETHEUS_LATENCY_BUCKETS=(.1,.2,.5,.6,.8,1.0,2.0,3.0,4.0,5.0,6.0,7.5,9.0,12.0,15.0,20.0,30.0,float("inf"))Monitoring your databasesSQLite, MySQL, and PostgreSQL databases can be monitored. Just
replace theENGINEproperty of your database, replacingdjango.db.backendswithdjango_prometheus.db.backends.DATABASES={'default':{'ENGINE':'django_prometheus.db.backends.sqlite3','NAME':os.path.join(BASE_DIR,'db.sqlite3'),},}Monitoring your cachesFilebased, memcached, redis caches can be monitored. Just replace
the cache backend to use the one provided by django_prometheusdjango.core.cache.backendswithdjango_prometheus.cache.backends.CACHES={'default':{'BACKEND':'django_prometheus.cache.backends.filebased.FileBasedCache','LOCATION':'/var/tmp/django_cache',}}Monitoring your modelsYou 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:classDog(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 theExportModelOperationsMixinas such:fromdjango_prometheus.modelsimportExportModelOperationsMixinclassDog(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"}anddjango_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_connectionanddjango_migrations_unapplied_by_connection. You may want to alert if
there are unapplied migrations.If you want to disable the Django migration metrics, set thePROMETHEUS_EXPORT_MIGRATIONSsetting to False.Monitoring and aggregating the metricsPrometheus is quite easy to set up. An example prometheus.conf to
scrape127.0.0.1:8001can be found inexamples/prometheus.Here's an example of a PromDash displaying some of the metrics
collected by django-prometheus:Adding your own metricsYou can add application-level metrics in your code by usingprometheus_clientdirectly. 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 oninstrumentationandnaming.Importing Django Prometheus using only local settingsIf 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_APPSMIDDLEWARE=\['django_prometheus.middleware.PrometheusBeforeMiddleware']+\MIDDLEWARE+\['django_prometheus.middleware.PrometheusAfterMiddleware']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:fromdjango.urlsimportinclude,pathurlpatterns=[]urlpatterns.append(path('prometheus/',include('django_prometheus.urls')))urlpatterns.append(path('',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"Adding custom labels to middleware (request/response) metricsYou can add application specific labels to metrics reported by the django-prometheus middleware.
This involves extending the classes defined in middleware.py.Extend the Metrics class and override theregister_metricmethod to add the application specific labels.Extend middleware classes, set the metrics_cls class attribute to the the extended metric class and override the label_metric method to attach custom metrics.See implementation example inthe test app