edit: you are right, it’s the I/O WAIT that it destroying my performance:
%Cpu(s): 0,3 us, 0,5 sy, 0,0 ni, 50,1 id, 49,0 wa, 0,0 hi, 0,1 si, 0,0 st
I could clearly see it using nmon > d > l > - such as was suggested by @SayCyberOnceMore. Not quite sure what to do about it, as it’s simply my sdb1 drive which is a Samsung 1TB 2.5" HDD. I have now ordered a 2TB SSD and maybe I am going to reinstall from scratch on that new drive as sda1. I realize that’s just treating the symptom and not the root cause, so I should probably also look for that root cause. But that’s for another Lemmy thread!
I really don’t understand what is causing this. I run a few very small containers, and everything is fine - but when I start something bigger like Photoprism, Immich, or even MariaDB or PostgreSQL, then something causes the CPU load to rise indefinitely.
Notably, the top command doesn’t show anything special, nothing eats RAM, nothing uses 100% CPU. And yet, the load is rising fast. If I leave it be, my ssh session loses connection. Hopping onto the host itself shows a load of over 50,or even over 70. I don’t grok how a system can even get that high at all.
My server is an older Intel i7 with 16GB RAM running Ubuntu22. 04 LTS.
How can I troubleshoot this, when ‘top’ doesn’t show any culprit and it does not seem to be caused by any one specific container?
(this makes me wonder how people can run anything at all off of a Raspberry Pi. My machine isn’t “beefy” but a Pi would be so much less.)
My money is also on IO. Outside of CPU and RAM, it’s the most likely resource to get saturated (especially if using rotational magnetic disks rather than an SSD, magnetic disks are going to be the performance limiter by a lot for many workloads), and also the one that OP said nothing about, suggesting it’s a blind spot for them.
In addition to the excellent command-line approaches suggested above, I recommend installing netdata on the box as it will show you a very comprehensive set of performance metrics without having to learn to collect each one on the CLI. A downside is that it will use RAM proportional to the data retention period, which if you’re swapping hard will be an issue. But even a few hours of data can be very useful and with 16gb of ram I feel like any swapping is likely to be a gross misconfiguration rather than true memory demand… and once that’s sorted dedicating a gig or two to observability will be a good investment.