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Podman deploy with quadlets
You can deploy Immich on Podman using quadlets.
Here are some sample rootless quadlet container files that can be placed in /etc/containers/systemd/users/${ID} where ID is the uid of whatever your rootless user is.
With Immich version 1.106.1 the microservices container no longer has to be separate from the immich server container. That being said, in the case where you would prefer to offload to a separate GPU accelerated VM this is still the preferred method. The quadlets provided below give a sample of said scenario. Feel free to remove the Environment variable that declares the API include and exclude if you prefer just the one container to run both.
Please note you'll need :z or :Z for selinux enabled hosts.
If you are doing hardware acceleration with NVIDIA make sure you follow the immich documentation including the appropriate NVIDIA Container Device Interface (https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/cdi-support.html) and adding the device (AddDevice=nvidia.com/gpu=0).
Sample Quadlet Files
It is recommended to run these rootless, and as such the ideal place is likely /etc/containers/systemd/users/${UID}
Universal
immich-database.container
[Unit]
Description=Immich Database
Requires=immich-redis.service
[Container]
AutoUpdate=registry
EnvironmentFile=${location_of_env_file}
Image=registry.hub.docker.com/tensorchord/pgvecto-rs:pg16-v0.2.1
Label=registry
Network=slirp4netns:port_handler=slirp4netns
PublishPort=5432:5432
Volume=${host_database_directory}:/var/lib/postgresql/data:z
Volume=${host_database_backup_directory}:/mnt/db_backup:z
Volume=/etc/localtime:/etc/localtime:ro
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
immich-redis.container
[Unit]
Description=Immich Redis
[Container]
AutoUpdate=registry
Image=registry.hub.docker.com/library/redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5
Label=registry
Network=slirp4netns:port_handler=slirp4netns
PublishPort=6379:6379
Timezone=America/Montreal
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
Alternatively you can use valkey
[Unit]
Description=Immich Keydb
[Container]
AutoUpdate=registry
HealthCmd=redis-cli ping || exit 1
HealthInterval=1m
HealthOnFailure=kill
Image=docker.io/valkey/valkey:latest
Label=registry
Network=host
PublishPort=6379:6379
Timezone=America/Montreal
Volume=/mnt/data01/immich-valkey:/data:z
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
immich-server.container
[Unit]
Description=Immich Server
Requires=immich-redis.service immich-database.service
[Container]
AutoUpdate=registry
EnvironmentFile=${location_of_env_file}
Environment=IMMICH_WORKERS_INCLUDE='api'
Image=ghcr.io/immich-app/immich-server:release
Label=registry
Network=slirp4netns:port_handler=slirp4netns
PublishPort=3000:3000
PublishPort=3001:3001
Volume=${host_upload_directory}:/usr/src/app/upload
Volume=/etc/localtime:/etc/localtime:ro
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
No Hardware Acceleration
immich-microservices.container
[Unit]
Description=Immich Microservices
Requires=immich-redis.service immich-database.service
[Container]
AutoUpdate=registry
EnvironmentFile=${location_of_env_file}
Environment=IMMICH_WORKERS_EXCLUDE='api'
Image=ghcr.io/immich-app/immich-server:release
Label=registry
Network=slirp4netns:port_handler=slirp4netns
PublishPort=3002:3002
Volume=${host_upload_directory}:/usr/src/app/upload:z
Volume=/etc/localtime:/etc/localtime:ro
#Exec=start.sh microservices
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
immich-ml.container
[Unit]
Description=Immich Machine Learning
Requires=immich-redis.service immich-database.service
[Container]
AutoUpdate=registry
EnvironmentFile=${location_of_env_file}
Image=ghcr.io/immich-app/immich-machine-learning:release
Label=registry
Network=slirp4netns:port_handler=slirp4netns
PublishPort=3003:3003
Volume=${cache_directory}:/cache:z
Volume=/etc/localtime:/etc/localtime:ro
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
Hardware Acceleration - NVIDIA CUDA
immich-microservices.container
[Unit]
Description=Immich Microservices
Requires=immich-redis.service immich-database.service
[Container]
AddDevice=/dev/dri:/dev/dri
AddDevice=nvidia.com/gpu=0
AutoUpdate=registry
EnvironmentFile=${location_of_env_file}
Environment=IMMICH_WORKERS_EXCLUDE='api'
Image=ghcr.io/immich-app/immich-server:${release} # This is for v118.0 and up
Label=registry
Network=slirp4netns:port_handler=slirp4netns
PublishPort=3002:3002
Volume=/mnt/data01/uploads:/usr/src/app/upload:z
Volume=/etc/localtime:/etc/localtime:ro
Unmask=/dev/dri:/dev/dri
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target
immich-ml.container
[Unit]
Description=Immich Machine Learning
Requires=mnt-data01.mount mnt-data01-uploads.mount
After==mnt-data01.mount mnt-data01-uploads.mount
[Container]
AddDevice=/dev/dri:/dev/dri
AddDevice=nvidia.com/gpu=0 # Make sure this matched your GPU ID
AutoUpdate=registry
EnvironmentFile=${location_of_env_file}
Image=ghcr.io/immich-app/immich-machine-learning:${release} # This is for v118.0 and up
Label=registry
Network=slirp4netns:port_handler=slirp4netns
#PublishPort=3003:3003
Volume=/mnt/data01/model-cache:/cache:z
Volume=/etc/localtime:/etc/localtime:ro
Unmask=/dev/dri:/dev/dri
[Service]
Restart=always
[Install]
WantedBy=multi-user.target default.target