django-prometheus VS client_python

We have a Django Graphene app working, and are gather Prometheus telemetry to monitor our end points. We are leveraging the Django Prometheus Middle Ware and are able to get telemetry and view it via Grafana. This all works and is awesome.

Thank you in advance.

[0] - https://github.com/korfuri/django-prometheus

Prometheus stores data in a custom format and provides it's own metrics SDK's. Uriel Corfa has done the heavy lifting for us by writing an app which hooks into the Django middleware, ORM and cache layer and automatically exposes metrics generalized metrics. All you need to do is to install and configure django-prometheus.

[2] https://github.com/korfuri/django-prometheus/blob/master/doc...

Here you go: https://stackoverflow.com/questions/75652326/celery-spawn-si...

Plus some adjacent discussion on GitHub: https://github.com/prometheus/client_python/issues/902

Hope that helps!

Prometheus, which is also a CNCF open source project, collects metrics data by scraping HTTP endpoints and then stores that data in a time series database that uses a multidimensional model. It’s a powerful tool for gathering metrics about your application and it also includes alerting functionality that you can use to notify your teams when issues come up. Prometheus includes a client library for Python.

We have a java one but the principle is the same. Install the Prometheus client ( https://github.com/prometheus/client_python) ,create the metrics you want, then push jmx settings to Prometheus.

The code above is copied from the official documentation of prometheus_client which simply creates a new metric named request_processing_seconds that measures the time spent on that particular request. We'll cover other types of metrics later in this post.

Just use the client? https://github.com/prometheus/client_python

I've experimented with the official Prometheus python client, i really really like the way they use decorators to instrument. I've tried to measure latency with multiple types of metrics (histogram, & summary), i see the value in both of them, but the one that between fits my objective is the histogram metric type. Great!

Now is a good time to expand your event loop by adding metrics collection of the event handler functions and also use that endpoint as a liveness probe. E.g. https://github.com/prometheus/client_python just add the event handled, success/error and the duration as a histogram (look for examples of tracking http requests served)

I've spent along time trying to figure out a bug that I'm facing while using Prometheus from its python client.

The official Prometheus Python client library makes this easy, no need to worry about the export file format.