homelab VS client_python

I do similar stuff but without windows https://gitlab.com/dekarl/homelab/-/blob/master/kubernetes-cluster.tf replace the maas stuff with hyperv

I do the configuration of my playground cluster like that. See https://gitlab.com/dekarl/homelab/-/tree/master/ (charts/configuration and helmfile-configuration)

My current homelab consists of amd64 thin clients, a NAS with MaaS and plain WiFi controlled power plugs. I'm still stuck at stateless workloads. Persistant volumes come after the Summer break.

I'm playing around with MaaS, too. Currently using microk8s, but looking for a replacement, like Talos.

Keeping the manifest updated should become a copypaste battle around now. Time to look into helmfile with one embedded chart for one handler and many instantiations. Start with one folder for the charts and two folders for the deployment to prod/stage. I started such a setup for my homelab at https://gitlab.com/dekarl/homelab/-/tree/master/

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.