TPLinkSmartPlugMetricExtractor VS Grafana

If UNA uses mongo db you can probably also use this but don’t ask me how. Since I’m not using a UDM and I won’t use it in the future, you can take a look at the examples provided by unifi-poller at https://unpoller.com/docs/poller/examples. You can do whatever you want with this data. You can also use Grafana/Prometheus/influx for all kind of data collection. I’m using it with Tibber (my power company) via my own importer (https://github.com/janwiesemann/tibberToInfluxDB), opnsense, proxmox, pihole, at work with our current project, and some cheap tp link smart plugs to also monitor my power consumption. This also uses my own importer/collector since all those python ones are slow and use to much resources (https://github.com/janwiesemann/TPLinkSmartPlugMetricExtractor)

I was also using a python script but it was extremely slow. Wrote a small Programm to fix this. https://github.com/janwiesemann/TPLinkSmartPlugMetricExtractor

You can check it out at: https://github.com/janwiesemann/TPLinkSmartPlugMetricExtractor

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.

Prometheus: Open-source monitoring system. Often used together with Grafana.

Grafana

Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.

So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:

In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana: