I have a decent 2 bay synology, but want to put all my docker images/ VMs running on a more powerful machine connected to the same LAN. Does it ever make sense to do the for media serving or will involving an extra device add too much complexity vs just serving from the NAS itself. I was hoping to have calibre/home assistant/tube type services, etc. all running off a mini PC with a Ryzen 7 and 64gb ram vs the NAS.
My Linux knowledge is intermediate; my networking knowledge is begintermediate, and I can generally follow documentation okay even if it’s a bit above my skill level.
Yeah, you definitely should run it on a separate machine. A home NAS itself probably shouldn’t be doing anything beyond serving files and basic maintenance. Using them for too much will reduce their ability to serve data fast enough. Just be sure the media server and NAS have appropriate network cards, preferably gigabit, though even 100Mbit probably is enough for most of your network isn’t already too busy, and ideally are connected to the same switch (again preferably gigabit) with good quality network cables.
I personally have them be the same device, but I have a DIY NAS, so my specs are already way overkill for regular NAS duty (it’s my old desktop PC).
Assuming your home network is fast, you should be fine to split them up. I personally designed my setup to make it easy to move things around should I decide to. I use Docker containers for everything, Caddy for TLS, and HAProxy set up at the edge to route based on domain, so moving a service to another device is just:
- copy relevant docker compose and Caddy config to new machine
- set up network mounts for anything the containers need
- point HAProxy (and my router DNS) to the new address
- test
I don’t have to remember where any of the config files are since they all live next to the compose file. I also don’t need to forget which directories need to be mounted because it’s already listed in the compose file.
So as long as you make it easy for yourself to move things around, it really doesn’t matter where your actual data lives.
