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Understand images, containers, and storage drivers

To use storage drivers effectively, you must understand how Docker builds and stores images. Then, you need an understanding of how these images are used in containers. Finally, you'll need a short introduction to the technologies that enable both images and container operations.

Images and containers rely on layers

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.

When you make a change inside a container by, for example, adding a new file to a container created from Ubuntu 15.04 image, you add a new layer on top of the underlying stack. This change creates a new writable layer containing the newly added file on top of the image layers. Each image layer is stored by a cryptographic hash over its contents and multiple images can share the same layers. The diagram below shows a container running the Ubuntu 15.04 image.

The major difference between a container and an image is this writable layer. All writes to the container that add new or modifying existing data are stored in this writable layer. When the container is deleted the writeable layer is also deleted. The image remains unchanged.

Because each container has its own thin writable container layer and all data is 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.

A storage driver is responsible for enabling and managing both the image layers and the writeable container layer. How a storage driver accomplishes these behaviors can vary. Two key technologies behind Docker image and container management are stackable image layers and copy-on-write (CoW).

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 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.

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 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.

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 thru sharing and copying.

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. It is a location on the host's filesystem.

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
6e6a100fa147: Pull complete
13c0c663a321: Pull complete
2bd276ed39d5: Pull complete
013f3d01d247: Pull complete
Digest: sha256:c7ecf33cef00ae34b131605c31486c91f5fd9a76315d075db2afd39d1ccdf3ed
Status: Downloaded newer image for ubuntu:15.04

From the output, you'll see that the command actually pulls 4 image layers. Each of the above lines lists an image layer and its UUID. The combination of these four layers makes up the ubuntu:15.04 Docker image.

The image layers are stored in the Docker host's local storage area. Typically, the local storage area is in the host's /var/lib/docker directory. Depending on which storage driver the local storage area may be in a different location. You can list the layers in the local storage area. The following example shows the storage as it appears under the AUFS storage driver:

$ sudo ls /var/lib/docker/aufs/layers
013f3d01d24738964bb7101fa83a926181d600ebecca7206dced59669e6e6778  2bd276ed39d5fcfd3d00ce0a190beeea508332f5aec3c6a125cc619a3fdbade6
13c0c663a321cd83a97f4ce1ecbaf17c2ba166527c3b06daaefe30695c5fcb8c  6e6a100fa147e6db53b684c8516e3e2588b160fd4898b6265545d5d4edb6796d

If you pull another image that shares some of the same image layers as the ubuntu:15.04 image, the Docker daemon recognize this, and only pull the layers it hasn't already stored. After the second pull, the two images will share any common image layers.

You can illustrate this now for yourself. Starting 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.

In an empty directory, create a simple Dockerfile that starts with the ubuntu:15.04 image.
```
 FROM ubuntu:15.04
```
Add a new file called "newfile" in the image's /tmp directory with the text "Hello world" in it.

When you are done, the Dockerfile contains two lines:

    FROM ubuntu:15.04

    RUN echo "Hello world" > /tmp/newfile

Save and close the file.

From a terminal in the same folder as your Dockerfile, run the following command:

 $ docker build -t changed-ubuntu .
 Sending build context to Docker daemon 2.048 kB
 Step 0 : FROM ubuntu:15.04
  ---> 013f3d01d247
 Step 1 : RUN echo "Hello world" > /tmp/newfile
  ---> Running in 2023460815df
  ---> 03b964f68d06
 Removing intermediate container 2023460815df
 Successfully built 03b964f68d06

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.

The output above shows a new image with image ID 03b964f68d06.

Run the docker images command to verify the new image is in the Docker host's local storage area.

 REPOSITORY          TAG                 IMAGE ID            CREATED             VIRTUAL SIZE
 changed-ubuntu      latest              03b964f68d06        33 seconds ago      131.4 MB
 ubuntu

Run the docker history command to see which image layers were used to create the new changed-ubuntu image.

 $ docker history changed-ubuntu
 IMAGE               CREATED              CREATED BY                                      SIZE                COMMENT
 03b964f68d06        About a minute ago   /bin/sh -c echo "Hello world" > /tmp/newfile    12 B                
 013f3d01d247        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:49710b44e2ae0edef4   131.4 MB

The docker history output shows the new 03b964f68d06 image layer at the top. You know that the 03b964f68d06 layer was 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 the make up the ubuntu:15.04 image as their UUIDs match.

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 it's four underlying layers with the ubuntu:15.04 image.

The docker history command also shows the size of each image layer. The 03b964f68d06 is only consuming 13 Bytes of disk space. Because all of the layers below it already exist on the Docker host and are shared with the ubuntu15:04 image, this means the entire changed-ubuntu image only consumes 13 Bytes of disk space.

This sharing of image layers is what makes Docker images and containers so space efficient.

Copying makes containers efficient

You learned earlier that a container 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:

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:

When a write operation occurs in a container, Docker uses the storage driver to perform a copy-on-write operation. The type of operation depends on the storage driver. For AUFS and OverlayFS storage drivers the copy-on-write operation is pretty much as follows:

Search through the layers for the file to update. The process starts at the top, newest layer and works down to the base layer one-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.
Modify the copy of the file in container's thin writable layer.

BTFS, 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.

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 containers thin writable top layer. If your container needs to write a lot of data, you can use a data volume.

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 container layer.

Let's see what happens if we spin up 5 containers based on our changed-ubuntu image we built earlier:

From a terminal on your Docker host, run the following docker run command 5 times.

 $ 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

This launches 5 containers based on the changed-ubuntu image. As the container is created, Docker adds a writable layer and assigns it a UUID. This is the value returned from the docker run command.

Run the docker ps command to verify the 5 containers are running.

 $ docker ps
 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

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.

List the contents of the local storage area.

 $ sudo ls containers
 0ad25d06bdf6fca0dedc38301b2aff7478b3e1ce3d1acd676573bba57cb1cfef  9280e777d109e2eb4b13ab211553516124a3d4d4280a0edfc7abf75c59024d47
 75bab0d54f3cf193cfdc3a86483466363f442fba30859f7dcd1b816b6ede82d4  a651680bd6c2ef64902e154eeb8a064b85c9abf08ac46f922ad8dfc11bb5cd8a
 8eb24b3b2d246f225b24f2fca39625aaad71689c392a7b552b78baf264647373

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.

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

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. A data volume is directory or file 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.

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. There is also a single shared data volume located at /data on the Docker host. This is mounted directly into both containers.

The data volume resides outside of the local storage area on the Docker host further reinforcing its independence from the storage driver's control. When a container is deleted, any data stored in shared data volumes persists on the Docker host.

For detailed information about data volumes Managing data in containers.

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