Looking at the Dockerfile for Postgres, you see that it declares a volume instruction:
VOLUME /var/lib/postgresql/data
Everytime you run a new Postgres container, without specifying a --volume
option, docker automatically creates a new volume. The volume is given a random name.
You can see all volumes by running the command:
docker volume ls
You can also inspect the files stored on the host by the volume, by inspecting the host path using:
docker volume inspect <volume-name>
So when you don't specify the --volume
option for the run command, docker create volumes for all volumes declared in the Dockerfile. This is mainly a safety if you forget to name your volume and the data shouldn't be lost.
Firstly: how do I make sure, if the container get's updated or
recreated that the postgres database from within the new container
references to the same data and not losing the reference to the
previously created anonymous volume.
If you want docker to use the same volume, you need to specify the --volume
option. Once specified, docker won't create a new volume and it will simply mount the existing volume onto the specified folder in the docker command.
As a best practice, name your volumes that have valuable data. For example:
docker run --volume postgresData:/var/lib/postgresql/data ...
If you run this command for the first time the volume postgresData
will be created and will backup /var/lib/postgresql/data
on the host. The second time you run it the same data backed up on the host will be mounted onto the container.
Secondly: how does this work with a yml file? is it possible to
reference multiple replicas of such a database container to one
volume?
Yes, volumes can be shared between multiple containers. You can mount the same volume onto multiple containers, and the containers will use the same files. Docker compose allows you to do that ...
However, beware that volumes are limited to the host they were created. When running containers on multiple machines, the volume needs to be accessible from all the machines. There are ways/tools to achieve that
but they are a bit complex. This is still a limitation to be addressed in Docker.