pushgateway VS django-prometheus

Pushgateway

In case the Custom Metric is related to a job or a short-living script, consider using Pushgateway.

So my idea is to have a python script that buckets data and then publishes it again using pushtogateway: https://github.com/prometheus/pushgateway

Is the cron job with a script for getting metric and pushing via https://github.com/prometheus/pushgateway the right way for this task?

The push gateway is a relatively simple service. There’s one main entry point file (main.go) and an api file (api.go) both at 279 lines log. There’s probably a dozen or so api endpoints, but the key one is the one where you post metrics, defined here

We are currently evaluating timeseries databases to build an internal tool for DORA metrics and just looking at prometheus. As tracking releases is more of a push based use case, I looked at pushgateway and the docs stated the following "The Pushgateway is not an event store. [...] tracking something like release events has to happen with some event-logging framework." here

Checked this out? https://github.com/prometheus/pushgateway

While I somehow understand Prometheus idea that pull is easier to scale than push I've had a bad luck with it.

First of all Prometheus doesn't even consider monitoring of long-running jobs other than pull way (which didn't make sense for me). There is push gateway [0] but clients libraries seem to consider it only for short-lived jobs where you can send the metrics at the end [1]. It seems I couldn't "push" from long living jobs trivially

Second when using it for example with django you have to be careful with how you handle multiprocessing that UWSGI/gunicorn does, see [2] - it has bitten me at leas once.

Comparing to push model where I can just push metrics to [3] statsd_exporter directly and be done with it, but support for statsd is lacking both in terms of frameworks (everyone seems to be migrating to native clients...) and functionality (you've to do labeling basically manually [4])

To sum up: Prometheus is really great when it works, until you try to go off-track (intentionally or not, see django [2]) then you see its all undiscovered and immature landscape

[0] https://github.com/prometheus/pushgateway

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...