Update [2025] on Docker inside LXD container with ZFS storage with GPU passthrough

LXD
1

Hey everyone

I realize that there has been some issues with docker on ZFS in the past. I just wanted to post a thread here incase anyone is searching the web for information on this.

It seems that with time ZFS now supports overlay2. I launched a container with the following profile settings

config:
  security.nesting: "true"
  security.syscalls.intercept.mknod: "true"
  security.syscalls.intercept.setxattr: "true"

Installed docker and ran a container. Everything worked, everything is fast.

here is docker info

Client:
 Version:    26.1.5
 Context:    default
 Debug Mode: false
 Plugins:
  buildx: Docker Buildx (Docker Inc.)
    Version:  v0.14.0
    Path:     /usr/libexec/docker/cli-plugins/docker-buildx

Server:
 Containers: 1
  Running: 1
  Paused: 0
  Stopped: 0
 Images: 1
 Server Version: 26.1.5
 Storage Driver: overlay2
  Backing Filesystem: zfs
  Supports d_type: true
  Using metacopy: false
  Native Overlay Diff: false
  userxattr: true
 Logging Driver: json-file
 Cgroup Driver: cgroupfs
 Cgroup Version: 2
 Plugins:
  Volume: local
  Network: bridge host ipvlan macvlan null overlay
  Log: awslogs fluentd gcplogs gelf journald json-file local splunk syslog
 Swarm: inactive
 Runtimes: io.containerd.runc.v2 runc
 Default Runtime: runc
 Init Binary: docker-init
 containerd version: 3a4de459a68952ffb703bbe7f2290861a75b6b67
 runc version: 2c9f5602f0ba3d9da1c2596322dfc4e156844890
 init version: 
 Security Options:
  apparmor
  seccomp
   Profile: builtin
  cgroupns
 Kernel Version: 6.8.0-51-generic
 Operating System: Alpine Linux v3.20
 OSType: linux
 Architecture: x86_64
 CPUs: 36
 Total Memory: 62.7GiB
 Name: test-docker
 ID: 31845754-aa9e-440b-b255-0cfd6a8816f7
 Docker Root Dir: /var/lib/docker
 Debug Mode: false
 Experimental: false
 Insecure Registries:
  127.0.0.0/8
 Live Restore Enabled: false

Here is what I ran

docker run -it --rm -d -p 8080:80 --name web nginx

I was also able to access the page served by the container from using curl -v http://lxd-container-ip:8080.

This is a very good out of the box ‘just works’ experience.

I hope this post can give an updated perspective on this issue. I also think Canonical should update the documentation here

This also opens up many opportunities. Imagine treating each of your lxd container as a ‘pod’ where you run multiple docker containers for a single app. This pretty much allows LXD to compete directly with K8s, but much more simple / lightweight / performant.

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2

great news, I’ve been creating containers which need docker as block storage (i.e. zvols) and formatting witrh ext4 or btrfs, which is super cumbersome for many reasons, but maybe I can stop now.

What version of zfs did you test with?

3

lxc info is returning the following:

  storage_supported_drivers:
  - name: zfs
    version: 2.2.2-0ubuntu9.1
    remote: false

I’m using lxd 5.21.2 via snap.

4

I’m happy to report that GPU passthrough also work out of the box.

I was able to run a podman container inside LXD container and have it successfully query nvidia-smi via Nvidia Container Toolkit

root@test-cuda-podman:~# podman run --rm --device nvidia.com/gpu=all --security-opt=label=disable ubuntu nvidia-smi
Mon Jan 20 23:59:39 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 555.42.02              Driver Version: 555.42.02      CUDA Version: 12.5     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  Quadro M2000                   Off |   00000000:03:00.0 Off |                  N/A |
| 56%   42C    P8             12W /   75W |       5MiB /   4096MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

Honestly right now I’m in shock at how simple this is. I didn’t have to do anything everything just worked out of the box. No more hacks / config etc…

I switched from docker to podman since it’s simpler and has support for Nvidia CDI protocol out of the box.

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