There are lots of places inside Docker (both at the engine level and container level) that use or work with storage.
In this post, I’ll take a broad look at a few of them, including: image storage, the copy-on-write mechanism, union file systems, storage drivers, and volumes.
You’ll need Docker installed locally on your machine if you want to try out some of the commands in this post. Check out the official docs for how to install Docker on Linux, or our previous post showing how to install Docker on a non-Linux machine.
Let’s dive in.
How are Docker images stored?
Let’s imagine we want to pull a Docker image from a registry, like so:
When you run this command, Docker will attempt to pull the
nginx image from the Docker Hub, which is a bit like GitHub but for Docker images. On the Docker Hub, you can see the descriptions of Docker images and take a look at their Dockerfiles, which contain the instructions that tell Docker how to build the image from the source.
Once the command completes, you should have the
nginx image in your local machine, being managed by your local Docker engine.
We can verify this is the case by listing the local images:
You should see something like this:
Now, if we want to launch an
nginx container, the process is very fast because we already have the
nginx image stored locally.
We can launch it like so:
This command maps port 80 of the container to port 8080 of the host machine. After it has run, you can connect to
localhost:8080 to verify that nginx responds.
But what’s going on in the background, as far as this container’s file system is concerned? To understand that, we need to look at the copy-on-write mechanism.
The Copy-on-Write Mechanism
When we launch an image, the Docker engine does not make a full copy of the already stored image. Instead, it uses something called the copy-on-write mechanism. This is a standard UNIX pattern that provides a single shared copy of some data, until the data is modified.
To do this, changes between the image and the running container are tracked. Just before any write operation is performed in the running container, a copy of the file that would be modified is placed on the writeable layer of the container, and that is where the write operation takes place. Hence the name, “copy-on-write”.
If this wasn’t happening, each time you launched an image, a full copy of the filesystem would have to be made. This would add time to the startup process and would end up using a lot of disk space.
Because of the copy-on-write mechanism, running containers can take less than 0.1 seconds to start up, and can occupy less than 1MB on disk. Compare this to Virtual Machines (VMs), which can take minutes and can occupy gigabytes of disk space, and you can see why Docker has seen such fast adoption.
But how is the copy-on-write mechanism implemented? To understand that, we need to take a look at the Union File System.
The Union File System
The Union File System (UFS) specialises in not storing duplicate data.
If two images have identical data, that data does not have to be recorded twice on disk. Instead, you can store the data once and then use it in many locations. This is possible with something called a layer.
Each layer is a file system, and as the name suggests, they can be layered on top of each other. Crucially, single layers containing shared files can be used in many images. This allows images to be constructed and deconstructed as needed, via the composition of different file system layers.
The layers that come with an image you pull from the Docker Hub are read-only. But when you run a container, you add a new layer on top of that. And the new layer is writable.
When you write to that layer, the entire stack is searched for the file you are writing to. And if a file is found, it is first copied to the writable layer. The write operation is then performed on that layer, not the underlying layer.
This works because when reading from a UFS volume, a search is done for the file that is being read. The first file that is found, reading from top to bottom, is used. So files on the writeable layer of your container are always used.
If we were to run thousands containers based on the same base layers we reap huge benefits in both startup time and disk space.
One example setup that would benefit is a web app that horizontally scales many identical web servers. Another would be a hosting company that provides the same basic image to all customers, and then only writes the data that customers add or change.
Docker has the benefit of being a complete product (the “batteries included” model) but also providing pluggability in case you want to add things.
By default, Docker ships with a AUFS storage driver. However, other storage drivers are pluggable such as OverlayFS, Device Mapper, BTRFS, VFS, and ZFS. They all implement image composition and copy-on-write mechanism, among other features.
To see what storage driver your Docker engine is using, run:
If you’re using the Docker default storage driver, you should see something like this:
Storage Driver: aufs line in this output. That means we’re using the stock AUFS driver.
That’s all we’ll say about storage drivers for now, as there’s way too much to cover in this post. If you want to know more, the official docs are a good place to start.
Let’s look at the way Docker works with app generated data.
A volume is a directory mounted inside a container that exists outside of the union file system. They are created via a Dockerfile, or the Docker CLI tool. The volume can map to an existing directory on the host machine, or remote NFS device.
The directory a volume maps to exists independently from any containers that mount it. This means you can create containers, write to volumes, and then destroy the containers again, without fear of losing any app data.
Volumes are great when you need to share data (or state) between containers, by mounting the same volume in multiple containers. Though take note: it’s important to implement locks or some other concurrent write access protection.
They’re also great when you want to share data between containers and the host machines, for example accessing source code.
Another common use is of volumes is when you’re dealing with large files, such as logs or databases. That’s because writing to a volume is faster than writing to the union file system, which uses the (IO expensive) copy-on-write mechanism.
To demonstrate the power of volumes and how to use them, let’s look at two scenarios.
Running a Container With a Volume Flag
Launch a container with
-v, the volume flag:
This creates a procedurally named directory (which we will look at shortly) on the host machine and then maps it to the
/code directory in the container.
You can see the volume has been created and mounted with this command:
You should see a long JSON-like output like this:
This output confirms the creation of the volume at the docker engine level as well as the mapping to the container’s
/code directory. Also take note of
/var/lib/docker/volumes/12f6[...]/_data, being the the volume path. We will use this path to access our data on the host machine.
Okay, next, grab a shell inside the container:
/code directory exists:
Change to the
Write something to a test file:
And exit the container:
Cool. So we just wrote some data to a file inside the volume mount inside our container. Let’s look inside that directory on the host machine we saw in the
docker inspect output above to see if we can find the data we wrote.
Login as the superuser, so you can access the Docker
Now, change to the directory listed in the previous
docker inspect output:
Check the contents of the directory:
Bingo! That’s the file we created inside the container.
You can even run
cat myfile if you want to check the contents are the same. Or additionally, you could modify the contents here and then grab a shell inside the container and check that it has been updated there.
Create Engine Level Volumes and Storage for Transient Containers
Since Docker 1.9, it is possible to create volumes using the Docker API.
You can create a volume via the Docker API like this:
We can check it worked like so:
Now, let’s run a little test:
What’s happening here?
First, we launch a
busybox container and mount the
myvolume volume to the
/data directory. Then we execute a command inside the container that writes “Hello” to the
/data/myfile.txt file. After that command has run, the container is stopped.
You can modify the above command to run
cat /data/myfile.txt if you want to read the data from inside the container at any point.
So, let’s see if we can find that file on our host machine.
Log in as the superuser:
Then change directory to the path listed as the
Mountpoint in the output from the
docker volume inspect myvolume command above.
And again, check the contents:
You can then read this file, write to it, and so on. And everything you do will be reflected inside the container. And vice versa.
In this post on Docker storage, we saw:
- How docker images are stored locally by the Docker engine
- How the copy-on-write mechanism and the union file system optimize storage and start up time for Docker containers
- The variety of storage drivers compatible with Docker
- How volumes provide shared persistent data for Docker containers
About the Author