Hi, I have a bunch of Raspberry Pies hosting all kinds of stuff and I want to have a monitoring solution for all of that. What would be your recommendations?
My goal is to be able to have an overview of CPU load, network load, CPU temp and to see what’s going on inside docker containers as I have everything dockerized. I’d like the solution to be open source. I want the solution to be web browser accessible and have nice load graphs with history. I don’t want to spend too much time setting it up.
All my Pies are running RaspberryOS, which is Debian based.
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Standard solution would be grafana + Prometheus on one server and a node exporter running on each pi. You then register the node exporters in Prometheus and use that as a data source for grafana. There you build a dashboard showing whatever metrics you want. It can also show some information about the Docker socket, like number of running/stopped containers and such.
I’m kind of loving Zabbix, but not sure if it’s the right solution for your needs. I’d say it would definitely work, but does take a bit of setup initially. This article is interesting, and seems to have a lot of what you want. Not sure if you want to do all of this. https://opensource.com/article/23/3/build-raspberry-pi-dashboard-appsmith
netdata is easy to set up and detects a lot of things on it’s own like databases and ntpd and…
Acronyms, initialisms, abbreviations, contractions, and other phrases which expand to something larger, that I’ve seen in this thread:
Fewer Letters More Letters DNS Domain Name Service/System PiHole Network-wide ad-blocker (DNS sinkhole) SAN Storage Area Network SSL Secure Sockets Layer, for transparent encryption TLS Transport Layer Security, supersedes SSL
3 acronyms in this thread; the most compressed thread commented on today has 15 acronyms.
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I didnt see it recommended yet, UptimeKuma is really simple if you just want to monitor the basics like if a url works or ping, tcp, etc without an agent.
It doesn’t do CPU/memory style metrics, but I find myself checking it more often because of how simple it is.
