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Docker Volume

· 4 min read

Overview

Docker containers are completely isolated by default, which means that data inside a container cannot be accessed from the host machine. This implies that the container's lifecycle is entirely dependent on its internal data. In simpler terms, when a container is removed, its data is also lost.

So, what should you do if you need to permanently store important data like logs or database information, independent of the container's lifecycle?

This is where volumes come into play.

Installing PostgreSQL Locally

Let's explore volumes by installing and using PostgreSQL in a simple example.

Without Using Volumes

1. Pull the Image

docker run -p 5432:5432 --name postgres -e POSTGRES_PASSWORD=1234 -d postgres

2. Connect to PostgreSQL

docker exec -it postgres psql -U postgres

3. Create a User

create user testuser password '1234' superuser;

4. Create a Database

create database testdb owner testuser;

You can also use tools like DBeaver or DataGrip to create users and databases.

When you're done, you can stop the container with docker stop postgres. Checking the container list with docker ps -a will show that the container is stopped but not removed.

$ docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
5c72a3d21021 postgres "docker-entrypoint.s…" 54 seconds ago Exited (0) 43 seconds ago postgres

In this state, you can restart the container with docker start postgres and the data will still be there.

Let's verify this.

Using the \list command in PostgreSQL will show that the testdb database still exists.

postgres=# \list
List of databases
Name | Owner | Encoding | Collate | Ctype | Access privileges
-----------+----------+----------+------------+------------+-----------------------
postgres | postgres | UTF8 | en_US.utf8 | en_US.utf8 |
template0 | postgres | UTF8 | en_US.utf8 | en_US.utf8 | =c/postgres +
| | | | | postgres=CTc/postgres
template1 | postgres | UTF8 | en_US.utf8 | en_US.utf8 | =c/postgres +
| | | | | postgres=CTc/postgres
testdb | testuser | UTF8 | en_US.utf8 | en_US.utf8 |
(4 rows)

But what happens if you completely remove the container using the docker rm option?

After running docker rm postgres and then docker run again, a new container is created, and you'll see that the testdb and user are gone.

$ docker rm postgres
postgres
$ docker run -p 5432:5432 --name postgres -e POSTGRES_PASSWORD=1234 -d postgres
67c5c39658f5a21a833fd2fab6058f509ddac110c72749092335eec5516177c2
$ docker exec -it postgres psql -U postgres
psql (14.4 (Debian 14.4-1.pgdg110+1))
Type "help" for help.

postgres=# \list
List of databases
Name | Owner | Encoding | Collate | Ctype | Access privileges
-----------+----------+----------+------------+------------+-----------------------
postgres | postgres | UTF8 | en_US.utf8 | en_US.utf8 |
template0 | postgres | UTF8 | en_US.utf8 | en_US.utf8 | =c/postgres +
| | | | | postgres=CTc/postgres
template1 | postgres | UTF8 | en_US.utf8 | en_US.utf8 | =c/postgres +
| | | | | postgres=CTc/postgres
(3 rows)

postgres=#

Using Volumes

First, create a volume.

$ docker volume create postgres
postgres

You can verify the volume creation with the ls command.

$ docker volume ls
DRIVER VOLUME NAME
local postgres

Now, run the PostgreSQL container with the created volume mounted.

$ docker run -p 5432:5432 --name postgres -e POSTGRES_PASSWORD=1234 -v postgres:/var/lib/postgresql/data -d postgres
002c552fe092da485ee30235d809c835eeb08bd7c00e6f91a2f172618682c48e

The subsequent steps are the same as those without using volumes. Now, even if you completely remove the container using docker rm, the data will remain in the volume and won't be lost.

As mentioned earlier, for long-term storage of log files or backup data, you can use volumes to ensure data persistence independent of the container's lifecycle.

Conclusion

We have explored what Docker volumes are and how to use them through a PostgreSQL example. Volumes are a key mechanism for data management in Docker containers. By appropriately using volumes based on the nature of the container, you can manage data safely and easily, which can significantly enhance development productivity once you get accustomed to it. For more detailed information, refer to the official documentation.

Reference