fourkeys VS pushgateway

Four Keys is an open source alternative by Google employees that has been halted earlier this year (but forks-friendly).

DORA metrics

We began tracking Dora metrics by saving all events from our SCM and CI/CD systems into postres DB. Guidance: https://github.com/GoogleCloudPlatform/fourkeys

For starters, there a number of tools such as Sleuth (disclaimer: am co-founder) that will measure the metrics for you. There are also open source options like Four Keys and many vendors like Gitlab also provide some or all metrics as well, though make sure they are measuring things as you expect.

I looked a lot for a tool that could help my team track these metrics. I knew that Jira, Gitlab, and some other tools implement these features but I was looking for something with a high level of customization, and not so coupled to a specific product (we use different systems for deployment, change, and incident) and one day I incidentally discovered FourKeys.

GoogleCloudPlatform/fourkeys is a software tool built by Google to generate insights from data based on the four core metrics mentioned above.

One solution we would recommend is the Four Keys project by Google.

Yep, in the process of productising Google’s Four Keys pattern. Pretty quick to stand up if you’re already on GCP.

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