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ddns | ||
demo | ||
develop | ||
dummy | ||
examples | ||
goproxy | ||
photoprism | ||
scripts | ||
tensorflow | ||
README.md |
Dockerfiles and Docker Compose Examples
Dockerfiles are text documents that contain all commands a user could call in a terminal to assemble an application image.
Docker Compose uses human-friendly YAML files to configure all application services so you can easily start them with a single command.
Why are we using Docker?
Containers are nothing new; Solaris Zones have been around for about 15 years, first released publicly in 2004. The chroot system call was introduced during development of Version 7 Unix in 1979. It is used ever since for hosting applications exposed to the public Internet.
Modern Linux containers are an incremental improvement. A main advantage of Docker is that application images can be easily made available to users via Internet. It provides a common standard across most operating systems and devices, which saves our team a lot of time that we can then spend more effectively, for example, providing support and developing one of the many features that users are waiting for.
Human-readable and versioned Dockerfiles as part of our public source code also help avoid surprises and "works for me" moments by enabling us to have the exact same environment everywhere in development and production.
Last but not least, virtually all file format parsers have vulnerabilities that just haven't been discovered yet. This is a known risk that can affect you even if your computer is not directly connected to the Internet. Running apps in a container with limited host access is an easy way to improve security without compromising performance and usability.
What about Virtual Machines?
A virtual machine running its own operating system provides more security, but typically has side effects such as lower performance and more difficult handling. You can also run Docker in a VM to get the best of both worlds. It's essentially what happens when you run dockerized applications on virtual cloud servers and operating systems other than Linux.
Alternatives
Building From Source
You can build and install PhotoPrism from the publicly available source code:
git clone https://github.com/photoprism/photoprism.git
cd photoprism
make all install
Missing build dependencies must be installed manually as shown in our human-readable and versioned Dockerfile. You often don't need to use the exact same versions, so it's possible to replace packages with what is available in your environment.
Note we don't have the resources to provide private users with dependencies and TensorFlow libraries for their personal environments. We therefore recommend learning Docker if your operating system supports it. Docker vastly simplifies installation and upgrades. It saves our team a lot of time that we can then spend more effectively.
Installation Packages
Everyone is invited to contribute by building and testing installation packages for Linux distributions and other operating systems! We currently don't have the resources to do this, as new versions are released several times a month and the long list of dependencies would lead to an enormous testing effort.
BSD Ports 😈
An unofficial port is available for FreeBSD / FreeNAS users.