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<!-- [metadata]>
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title = "Understand images, containers, and storage drivers"
description = "Learn the technologies that support storage drivers."
keywords = ["container, storage, driver, AUFS, btfs, devicemapper,zvfs"]
[menu.main]
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parent = "engine_driver"
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weight = -2
+++
<![end-metadata]-->
# Understand images, containers, and storage drivers
To use storage drivers effectively, you must understand how Docker builds and
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stores images. Then, you need an understanding of how these images are used by
containers. Finally, you'll need a short introduction to the technologies that
enable both images and container operations.
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## Images and layers
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Each Docker image references a list of read-only layers that represent
filesystem differences. Layers are stacked on top of each other to form a base
for a container's root filesystem. The diagram below shows the Ubuntu 15.04
image comprising 4 stacked image layers.
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![](images/image-layers.jpg)
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The Docker storage driver is responsible for stacking these layers and
providing a single unified view.
When you create a new container, you add a new, thin, writable layer on top of
the underlying stack. This layer is often called the "container layer". All
changes made to the running container - such as writing new files, modifying
existing files, and deleting files - are written to this thin writable
container layer. The diagram below shows a container based on the Ubuntu 15.04
image.
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![](images/container-layers.jpg)
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### Content addressable storage
Docker 1.10 introduced a new content addressable storage model. This is a
completely new way to address image and layer data on disk. Previously, image
and layer data was referenced and stored using a a randomly generated UUID. In
the new model this is replaced by a secure *content hash* .
The new model improves security, provides a built-in way to avoid ID
collisions, and guarantees data integrity after pull, push, load, and save
operations. It also enables better sharing of layers by allowing many images to
freely share their layers even if they didn’ t come from the same build.
The diagram below shows an updated version of the previous diagram,
highlighting the changes implemented by Docker 1.10.
![](images/container-layers-cas.jpg)
As can be seen, all image layer IDs are cryptographic hashes, whereas the
container ID is still a randomly generated UUID.
There are several things to note regarding the new model. These include:
1. Migration of existing images
2. Image and layer filesystem structures
Existing images, those created and pulled by earlier versions of Docker, need
to be migrated before they can be used with the new model. This migration
involves calculating new secure checksums and is performed automatically the
first time you start an updated Docker daemon. After the migration is complete,
all images and tags will have brand new secure IDs.
Although the migration is automatic and transparent, it is computationally
intensive. This means it and can take time if you have lots of image data.
During this time your Docker daemon will not respond to other requests.
A migration tool exists that allows you to migrate existing images to the new
format before upgrading your Docker daemon. This means that upgraded Docker
daemons do not need to perform the migration in-band, and therefore avoids any
associated downtime. It also provides a way to manually migrate existing images
so that they can be distributed to other Docker daemons in your environment
that are already running the latest versions of Docker.
The migration tool is provided by Docker, Inc., and runs as a container. You
can download it from [https://github.com/docker/v1.10-migrator/releases ](https://github.com/docker/v1.10-migrator/releases ).
While running the "migrator" image you need to expose your Docker host's data
directory to the container. If you are using the default Docker data path, the
command to run the container will look like this
$ sudo docker run --rm -v /var/lib/docker:/var/lib/docker docker/v1.10-migrator
If you use the `devicemapper` storage driver, you will need to include the
`--privileged` option so that the container has access to your storage devices.
#### Migration example
The following example shows the migration tool in use on a Docker host running
version 1.9.1 of the Docker daemon and the AUFS storage driver. The Docker host
is running on a **t2.micro** AWS EC2 instance with 1 vCPU, 1GB RAM, and a
single 8GB general purpose SSD EBS volume. The Docker data directory
(`/var/lib/docker`) was consuming 2GB of space.
$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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jenkins latest 285c9f0f9d3d 17 hours ago 708.5 MB
mysql latest d39c3fa09ced 8 days ago 360.3 MB
mongo latest a74137af4532 13 days ago 317.4 MB
postgres latest 9aae83d4127f 13 days ago 270.7 MB
redis latest 8bccd73928d9 2 weeks ago 151.3 MB
centos latest c8a648134623 4 weeks ago 196.6 MB
ubuntu 15.04 c8be1ac8145a 7 weeks ago 131.3 MB
$ du -hs /var/lib/docker
2.0G /var/lib/docker
$ time docker run --rm -v /var/lib/docker:/var/lib/docker docker/v1.10-migrator
Unable to find image 'docker/v1.10-migrator:latest' locally
latest: Pulling from docker/v1.10-migrator
ed1f33c5883d: Pull complete
b3ca410aa2c1: Pull complete
2b9c6ed9099e: Pull complete
dce7e318b173: Pull complete
Digest: sha256:bd2b245d5d22dd94ec4a8417a9b81bb5e90b171031c6e216484db3fe300c2097
Status: Downloaded newer image for docker/v1.10-migrator:latest
time="2016-01-27T12:31:06Z" level=debug msg="Assembling tar data for 01e70da302a553ba13485ad020a0d77dbb47575a31c4f48221137bb08f45878d from /var/lib/docker/aufs/diff/01e70da302a553ba13485ad020a0d77dbb47575a31c4f48221137bb08f45878d"
time="2016-01-27T12:31:06Z" level=debug msg="Assembling tar data for 07ac220aeeef9febf1ac16a9d1a4eff7ef3c8cbf5ed0be6b6f4c35952ed7920d from /var/lib/docker/aufs/diff/07ac220aeeef9febf1ac16a9d1a4eff7ef3c8cbf5ed0be6b6f4c35952ed7920d"
< snip >
time="2016-01-27T12:32:00Z" level=debug msg="layer dbacfa057b30b1feaf15937c28bd8ca0d6c634fc311ccc35bd8d56d017595d5b took 10.80 seconds"
real 0m59.583s
user 0m0.046s
sys 0m0.008s
The Unix `time` command prepends the `docker run` command to produce timings
for the operation. As can be seen, the overall time taken to migrate 7 images
comprising 2GB of disk space took approximately 1 minute. However, this
included the time taken to pull the `docker/v1.10-migrator` image
(approximately 3.5 seconds). The same operation on an m4.10xlarge EC2 instance
with 40 vCPUs, 160GB RAM and an 8GB provisioned IOPS EBS volume resulted in the
following improved timings:
real 0m9.871s
user 0m0.094s
sys 0m0.021s
This shows that the migration operation is affected by the hardware spec of the
machine performing the migration.
## Container and layers
The major difference between a container and an image is the top writable
layer. All writes to the container that add new or modify existing data are
stored in this writable layer. When the container is deleted the writable layer
is also deleted. The underlying image remains unchanged.
Because each container has its own thin writable container layer, and all
changes are stored this container layer, this means that multiple containers
can share access to the same underlying image and yet have their own data
state. The diagram below shows multiple containers sharing the same Ubuntu
15.04 image.
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![](images/sharing-layers.jpg)
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The Docker storage driver is responsible for enabling and managing both the
image layers and the writable container layer. How a storage driver
accomplishes these can vary between drivers. Two key technologies behind Docker
image and container management are stackable image layers and copy-on-write
(CoW).
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## The copy-on-write strategy
Sharing is a good way to optimize resources. People do this instinctively in
daily life. For example, twins Jane and Joseph taking an Algebra class at
different times from different teachers can share the same exercise book by
passing it between each other. Now, suppose Jane gets an assignment to complete
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the homework on page 11 in the book. At that point, Jane copies page 11,
completes the homework, and hands in her copy. The original exercise book is
unchanged and only Jane has a copy of the changed page 11.
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Copy-on-write is a similar strategy of sharing and copying. In this strategy,
system processes that need the same data share the same instance of that data
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rather than having their own copy. At some point, if one process needs to
modify or write to the data, only then does the operating system make a copy of
the data for that process to use. Only the process that needs to write has
access to the data copy. All the other processes continue to use the original
data.
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Docker uses a copy-on-write technology with both images and containers. This
CoW strategy optimizes both image disk space usage and the performance of
container start times. The next sections look at how copy-on-write is leveraged
with images and containers through sharing and copying.
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### Sharing promotes smaller images
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This section looks at image layers and copy-on-write technology. All image and
container layers exist inside the Docker host's *local storage area* and are
managed by the storage driver. On Linux-based Docker hosts this is usually
located under `/var/lib/docker/` .
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The Docker client reports on image layers when instructed to pull and push
images with `docker pull` and `docker push` . The command below pulls the
`ubuntu:15.04` Docker image from Docker Hub.
$ docker pull ubuntu:15.04
15.04: Pulling from library/ubuntu
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1ba8ac955b97: Pull complete
f157c4e5ede7: Pull complete
0b7e98f84c4c: Pull complete
a3ed95caeb02: Pull complete
Digest: sha256:5e279a9df07990286cce22e1b0f5b0490629ca6d187698746ae5e28e604a640e
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Status: Downloaded newer image for ubuntu:15.04
From the output, you'll see that the command actually pulls 4 image layers.
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Each of the above lines lists an image layer and its UUID or cryptographic
hash. The combination of these four layers makes up the `ubuntu:15.04` Docker
image.
Each of these layers is stored in its own directory inside the Docker host's
local storage are.
Versions of Docker prior to 1.10 stored each layer in a directory with the same
name as the image layer ID. However, this is not the case for images pulled
with Docker version 1.10 and later. For example, the command below shows an
image being pulled from Docker Hub, followed by a directory listing on a host
running version 1.9.1 of the Docker Engine.
$ docker pull ubuntu:15.04
15.04: Pulling from library/ubuntu
47984b517ca9: Pull complete
df6e891a3ea9: Pull complete
e65155041eed: Pull complete
c8be1ac8145a: Pull complete
Digest: sha256:5e279a9df07990286cce22e1b0f5b0490629ca6d187698746ae5e28e604a640e
Status: Downloaded newer image for ubuntu:15.04
$ ls /var/lib/docker/aufs/layers
47984b517ca9ca0312aced5c9698753ffa964c2015f2a5f18e5efa9848cf30e2
c8be1ac8145a6e59a55667f573883749ad66eaeef92b4df17e5ea1260e2d7356
df6e891a3ea9cdce2a388a2cf1b1711629557454fd120abd5be6d32329a0e0ac
e65155041eed7ec58dea78d90286048055ca75d41ea893c7246e794389ecf203
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Notice how the four directories match up with the layer IDs of the downloaded
image. Now compare this with the same operations performed on a host running
version 1.10 of the Docker Engine.
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$ docker pull ubuntu:15.04
15.04: Pulling from library/ubuntu
1ba8ac955b97: Pull complete
f157c4e5ede7: Pull complete
0b7e98f84c4c: Pull complete
a3ed95caeb02: Pull complete
Digest: sha256:5e279a9df07990286cce22e1b0f5b0490629ca6d187698746ae5e28e604a640e
Status: Downloaded newer image for ubuntu:15.04
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$ ls /var/lib/docker/aufs/layers/
1d6674ff835b10f76e354806e16b950f91a191d3b471236609ab13a930275e24
5dbb0cbe0148cf447b9464a358c1587be586058d9a4c9ce079320265e2bb94e7
bef7199f2ed8e86fa4ada1309cfad3089e0542fec8894690529e4c04a7ca2d73
ebf814eccfe98f2704660ca1d844e4348db3b5ccc637eb905d4818fbfb00a06a
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See how the four directories do not match up with the image layer IDs pulled in
the previous step.
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Despite the differences between image management before and after version 1.10,
all versions of Docker still allow images to share layers. For example, If you
`pull` an image that shares some of the same image layers as an image that has
already been pulled, the Docker daemon recognizes this, and only pulls the
layers it doesn't already have stored locally. After the second pull, the two
images will share any common image layers.
You can illustrate this now for yourself. Starting with the `ubuntu:15.04`
image that you just pulled, make a change to it, and build a new image based on
the change. One way to do this is using a `Dockerfile` and the `docker build`
command.
1. In an empty directory, create a simple `Dockerfile` that starts with the
2. ubuntu:15.04 image.
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FROM ubuntu:15.04
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2. Add a new file called "newfile" in the image's `/tmp` directory with the
3. text "Hello world" in it.
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When you are done, the `Dockerfile` contains two lines:
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FROM ubuntu:15.04
RUN echo "Hello world" > /tmp/newfile
3. Save and close the file.
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4. From a terminal in the same folder as your `Dockerfile` , run the following
5. command:
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$ docker build -t changed-ubuntu .
Sending build context to Docker daemon 2.048 kB
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Step 1 : FROM ubuntu:15.04
---> 3f7bcee56709
Step 2 : RUN echo "Hello world" > /tmp/newfile
---> Running in d14acd6fad4e
---> 94e6b7d2c720
Removing intermediate container d14acd6fad4e
Successfully built 94e6b7d2c720
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> **Note:** The period (.) at the end of the above command is important. It
> tells the `docker build` command to use the current working directory as
> its build context.
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The output above shows a new image with image ID `94e6b7d2c720` .
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5. Run the `docker images` command to verify the new `changed-ubuntu` image is
6. in the Docker host's local storage area.
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REPOSITORY TAG IMAGE ID CREATED SIZE
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changed-ubuntu latest 03b964f68d06 33 seconds ago 131.4 MB
ubuntu 15.04 013f3d01d247 6 weeks ago 131.3 MB
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6. Run the `docker history` command to see which image layers were used to
7. create the new `changed-ubuntu` image.
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$ docker history changed-ubuntu
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IMAGE CREATED CREATED BY SIZE COMMENT
94e6b7d2c720 2 minutes ago /bin/sh -c echo "Hello world" > /tmp/newfile 12 B
3f7bcee56709 6 weeks ago /bin/sh -c #(nop) CMD ["/bin/bash"] 0 B
< missing > 6 weeks ago /bin/sh -c sed -i 's/^#\s*\(deb.*universe\)$/ 1.879 kB
< missing > 6 weeks ago /bin/sh -c echo '#!/bin/sh' > /usr/sbin/polic 701 B
< missing > 6 weeks ago /bin/sh -c #(nop) ADD file:8e4943cd86e9b2ca13 131.3 MB
The `docker history` output shows the new `94e6b7d2c720` image layer at the
top. You know that this is the new image layer added because it was created
by the `echo "Hello world" > /tmp/newfile` command in your `Dockerfile` .
The 4 image layers below it are the exact same image layers
that make up the `ubuntu:15.04` image.
> **Note:** Under the content addressable storage model introduced with Docker
> 1.10, image history data is no longer stored in a config file with each image
> layer. It is now stored as a string of text in a single config file that
> relates to the overall image. This can result in some image layers showing as
> "missing" in the output of the `docker history` command. This is normal
> behaviour and can be ignored.
>
> You may hear images like these referred to as *flat images*.
Notice the new `changed-ubuntu` image does not have its own copies of every
layer. As can be seen in the diagram below, the new image is sharing its four
underlying layers with the `ubuntu:15.04` image.
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![](images/saving-space.jpg)
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The `docker history` command also shows the size of each image layer. As you
can see, the `94e6b7d2c720` layer is only consuming 12 Bytes of disk space.
This means that the `changed-ubuntu` image we just created is only consuming an
additional 12 Bytes of disk space on the Docker host - all layers below the
`94e6b7d2c720` layer already exist on the Docker host and are shared by other
images.
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This sharing of image layers is what makes Docker images and containers so
space efficient.
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### Copying makes containers efficient
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You learned earlier that a container is a Docker image with a thin writable,
container layer added. The diagram below shows the layers of a container based
on the `ubuntu:15.04` image:
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![](images/container-layers-cas.jpg)
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All writes made to a container are stored in the thin writable container layer.
The other layers are read-only (RO) image layers and can't be changed. This
means that multiple containers can safely share a single underlying image. The
diagram below shows multiple containers sharing a single copy of the
`ubuntu:15.04` image. Each container has its own thin RW layer, but they all
share a single instance of the ubuntu:15.04 image:
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![](images/sharing-layers.jpg)
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When an existing file in a container is modified, Docker uses the storage
driver to perform a copy-on-write operation. The specifics of operation depends
on the storage driver. For the AUFS and OverlayFS storage drivers, the
copy-on-write operation is pretty much as follows:
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* Search through the image layers for the file to update. The process starts
at the top, newest layer and works down to the base layer one layer at a
time.
* Perform a "copy-up" operation on the first copy of the file that is found. A
"copy up" copies the file up to the container's own thin writable layer.
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* Modify the *copy of the file* in container's thin writable layer.
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Btrfs, ZFS, and other drivers handle the copy-on-write differently. You can
read more about the methods of these drivers later in their detailed
descriptions.
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Containers that write a lot of data will consume more space than containers
that do not. This is because most write operations consume new space in the
container's thin writable top layer. If your container needs to write a lot of
data, you should consider using a data volume.
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A copy-up operation can incur a noticeable performance overhead. This overhead
is different depending on which storage driver is in use. However, large files,
lots of layers, and deep directory trees can make the impact more noticeable.
Fortunately, the operation only occurs the first time any particular file is
modified. Subsequent modifications to the same file do not cause a copy-up
operation and can operate directly on the file's existing copy already present
in the container layer.
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Let's see what happens if we spin up 5 containers based on our `changed-ubuntu`
image we built earlier:
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1. From a terminal on your Docker host, run the following `docker run` command
5 times.
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$ docker run -dit changed-ubuntu bash
75bab0d54f3cf193cfdc3a86483466363f442fba30859f7dcd1b816b6ede82d4
$ docker run -dit changed-ubuntu bash
9280e777d109e2eb4b13ab211553516124a3d4d4280a0edfc7abf75c59024d47
$ docker run -dit changed-ubuntu bash
a651680bd6c2ef64902e154eeb8a064b85c9abf08ac46f922ad8dfc11bb5cd8a
$ docker run -dit changed-ubuntu bash
8eb24b3b2d246f225b24f2fca39625aaad71689c392a7b552b78baf264647373
$ docker run -dit changed-ubuntu bash
0ad25d06bdf6fca0dedc38301b2aff7478b3e1ce3d1acd676573bba57cb1cfef
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This launches 5 containers based on the `changed-ubuntu` image. As each
container is created, Docker adds a writable layer and assigns it a random
UUID. This is the value returned from the `docker run` command.
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2. Run the `docker ps` command to verify the 5 containers are running.
$ docker ps
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CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
0ad25d06bdf6 changed-ubuntu "bash" About a minute ago Up About a minute stoic_ptolemy
8eb24b3b2d24 changed-ubuntu "bash" About a minute ago Up About a minute pensive_bartik
a651680bd6c2 changed-ubuntu "bash" 2 minutes ago Up 2 minutes hopeful_turing
9280e777d109 changed-ubuntu "bash" 2 minutes ago Up 2 minutes backstabbing_mahavira
75bab0d54f3c changed-ubuntu "bash" 2 minutes ago Up 2 minutes boring_pasteur
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The output above shows 5 running containers, all sharing the
`changed-ubuntu` image. Each `CONTAINER ID` is derived from the UUID when
creating each container.
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3. List the contents of the local storage area.
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$ sudo ls /var/lib/docker/containers
0ad25d06bdf6fca0dedc38301b2aff7478b3e1ce3d1acd676573bba57cb1cfef
9280e777d109e2eb4b13ab211553516124a3d4d4280a0edfc7abf75c59024d47
75bab0d54f3cf193cfdc3a86483466363f442fba30859f7dcd1b816b6ede82d4
a651680bd6c2ef64902e154eeb8a064b85c9abf08ac46f922ad8dfc11bb5cd8a
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8eb24b3b2d246f225b24f2fca39625aaad71689c392a7b552b78baf264647373
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Docker's copy-on-write strategy not only reduces the amount of space consumed
by containers, it also reduces the time required to start a container. At start
time, Docker only has to create the thin writable layer for each container.
The diagram below shows these 5 containers sharing a single read-only (RO)
copy of the `changed-ubuntu` image.
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![](images/shared-uuid.jpg)
If Docker had to make an entire copy of the underlying image stack each time it
started a new container, container start times and disk space used would be
significantly increased.
## Data volumes and the storage driver
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When a container is deleted, any data written to the container that is not
stored in a *data volume* is deleted along with the container.
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A data volume is a directory or file in the Docker host's filesystem that is
mounted directly into a container. Data volumes are not controlled by the
storage driver. Reads and writes to data volumes bypass the storage driver and
operate at native host speeds. You can mount any number of data volumes into a
container. Multiple containers can also share one or more data volumes.
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The diagram below shows a single Docker host running two containers. Each
container exists inside of its own address space within the Docker host's local
storage area (`/var/lib/docker/...`). There is also a single shared data
volume located at `/data` on the Docker host. This is mounted directly into
both containers.
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![](images/shared-volume.jpg)
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Data volumes reside outside of the local storage area on the Docker host,
further reinforcing their independence from the storage driver's control. When
a container is deleted, any data stored in data volumes persists on the Docker
host.
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For detailed information about data volumes
[Managing data in containers ](https://docs.docker.com/userguide/dockervolumes/ ).
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## Related information
* [Select a storage driver ](selectadriver.md )
* [AUFS storage driver in practice ](aufs-driver.md )
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* [Btrfs storage driver in practice ](btrfs-driver.md )
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* [Device Mapper storage driver in practice ](device-mapper-driver.md )