System requirements for low-end UX #4364
Replies: 4 comments 2 replies
-
Thank you for sharing your experiences. We are looking forward to even further optimization of Immich to serve use case such as yours! |
Beta Was this translation helpful? Give feedback.
-
@davidecavestro |
Beta Was this translation helpful? Give feedback.
-
I confirm I only run this script for cgroup limits, but as root user. |
Beta Was this translation helpful? Give feedback.
-
Thanks for sharing. I will give this a try as I'm experiencing problems when attempting to run Immich on my QNAP TS-251+ NAS. It's a Intel® Celeron® J1900 4-core 2-2.4Ghz CPU with 8GB of DDR3L memory. The machine learning service seems to eat all resources as soon as I upload my first batch of photos, ultimately suffocating all containers. |
Beta Was this translation helpful? Give feedback.
-
While still far from having a fine-tuned config to share, I certainly have Immich running on a NAS equipped with just 4Gb of RAM and a dual-core Celeron N4505: both face recognition and typesense are enabled.
So I would like to share my experience and collect feedback, so that other low-end users give Immich a try, as it really works like a charm even on devices like mine.
The first time I considered running Immich on this hardware, I read the official docs and decided to give up: minimum requirements were not met.
Then - after a lot of headaches with other software - I gave it a try and: KABOOM! I started with ML and search disabled, then enabled them.
Now my configuration is still not fine-tuned, but for sure docker is running Immich like this:
This is an excerpt of my compose.yml:
But please note that I also set some global cgroup limits to 3.2Gb of memory and 1.8 CPU cores for the whole docker stuff, so that - in case of spikes - single limits are further bounded by global ones:
At the moment this system is also running a jellyfin instance and some scheduled rclone copy tasks.
TBH I cannot assure containers are never killed this way: maybe it could happen if I launch a lot of concurrent batch jobs.
THat said I'm sure this way it just works properly for me, and I will refine it if needed.
Anyone tried something similar?
What was the oucome?
Beta Was this translation helpful? Give feedback.
All reactions