Almost always, working with docker means, using images of other engineers as a base. Then we put our configurations on the top of these base images and serve our own purpose. This time, I am going to demonstrate, how to bake our own docker image.
To make a docker image developer-friendly, we use tagging on these images. I will also discuss how Docker uses the caching mechanism on image building to provide robust performance.
Create a Custom Image
To create our own image, we have to do the followings,
- Create a
dockerfile
- Once a
dockerfile
is created, we will pass it to thedocker client
- This
docker client
will provide theimage
to thedocker server
- The
docker-server
will make theimage
. If we push the image to the Docker hub, then other engineers can use it.
A
dockerfile
is a plain text file. It contains all the configs along with the startup commands to define how a dockercontainer
should behave. It determine what programs should be inside the container and how will these program will work around in thecontainer
star up
For each docker file
, we can find the following similar pattern,
- A
base image
- Some config to install additional programs and dependencies that are required to create and execute the container program
- A start-up command, that will be executed the moment a container start
Docker server
does the most of heavy lifting while creating aimage
. It takes the docker file, go through the configuration and build the useableimage
Hands-On
Let’s create our own docker image
that will run a redis-server
. We will do the following procedures
- Define base
image
- Download and install the
dependencies
- Instruct the images initial behavior
First, we will go through a couple of commands, codes, and scripts. If that does not make sense, please seat tight, I will explain every single line in the next section.
So,
- First, create a file named
Dockerfile
touch Dockerfile
- In the
Dockerfile
, add a base imageFROM alpine
- Download the dependency
RUN apk add --update redis
- Define the initial command
CMD ["redis-server"]
Finally our Dockerfile
should be the following
FROM alpine
RUN apk add --update redis
CMD ["redis-server"]
Code language: CSS (css)
Now let’s build the container
docker build .
This will create the image and return the image_id
.
Now we can run the container
from the image_id
using the followings,
docker run image_id
This will run the Redis server.
Dockerfile
is a plain file with no extension
Dockerfile Teardown
We just going through the process of creating a docker image. But we have not explained what really happens there. Now let’s explain what actually we have done inside the Dockerfile
configuration.
We ran 3 commands to build the image, and all three have a very similar pattern. Each command start with FROM
, RUN
or CMD
, called docker instruction
and they took some arguments
.
The
FROM
instruction specify adocker image
we want to use as base. While we are preparing our custom image, theRUN
execute some commands. TheCMD
specify, what should run on startup when our image will be used to create a newcontainer
.
Every line of configuration we are going to add inside the Dockerfile
will always start with an instruction
A base image is an initial set of programs that can be used to to further customize the the image.
Alpine
is a base image that comes with a package manager namedapk
(Apache Package Manager).apk
can be used to download theredis-server
and install in the system.
With FROM alpine
, we are using an initial operating system named alpine
. This alpine
the operating system has a couple of preinstalled programs, that are very much useful for what we are trying to accomplish. Since we are here to create redis server
and we need to install some dependencies, alpine
has these tools and programs preinstalled like apk
.
With RUN apk add --update redis
we download and install the server. Here apk
is nothing related to the docker
. It’s a dependency manager preinstalled in the base image
, download and install the redis
server.
The CMD ["redis-server"]
ensure, when we create a container from this docker image
, the Redis server will be started using redis-server
command.
Image build process
To build an image from the Dockerfile
, we use
docker build .
This ships our Dockerfile
to the docker client
. build
is responsible for taking the Dockerfile
and build an image
out of it.
The .
is the build context. The build context contains all the set of files and folders that belongs to our project needs to wrap or encapsulate in our docker container
.
If we notice the logs of the docker build .
, we can see except the first instruction FROM alpine
, every other instruction has an intermediary container
that being removed automatically.
This means, except for the first step, each step took the container from the previous step, and the step itself acts as the startup instruction. Then when the step is done, it simply passes the updated file system snapshot and removes the temporary container from itself.
For the last step, it took the container from the previous step, and do not run itself as the start-up command. Instead, it only set itself as the first instruction and ensure if someone in the future creates and run the container
out of the image, it then executes this last step as the startup instruction
.
tldr; For each step, except first one, we take the
image
from the previous step, create a temporary container, execute instructions, make changes, took the snapshot of the file system and return the file system output as output, so it can be used as the image for the next step. For last step, the final instruction is considered as thestart-up
instruction of thedocker container
.
Rebuild image from the cache
Let’s update the Dockerfile
with an additional command
RUN apk add --update gcc
Now the Dockerfile
should be like
FROM alpine
RUN apk add --update redis
RUN apk add --update gcc
CMD ["redis-server"]
Code language: CSS (css)
Let’s build an image out of this Dockerfile
,
docker build .
If we observer the logs
closely, we see, in the second step, it does not create a intermediary container
from the previous step. Instead, it is using the cache. So we do not need to install the redis-server
multiple times. This gives the docker robustness and faster build performance.
From the instruction RUN apk add --update gcc
it will create the intermediary container
and since the file snapshot is being changed, it will do the same from the next steps.
If we build the image from the same Dockerfile
for the 3rd time, it will take all the changes from the cache instead of the intermediary container
.
An
intermediary container
is created from the previous step image and use to run current instruction, make changes, take the snapshot of the new changed file system and got removed. This snapshot is being used for the next step to create anotherintermediary container
and goes on.Altering the instruction sequence will not use the cache.
Tagging a docker image
Till now, we have created image
from the Dockerfile
and getting an image_id
.
When we want a name instead of an image_id
we can use the tagging
.
To get a name, after a image
being created, we can use the following
docker build -t user_name/image_name:version_number .
This will return
Successfully tagged user_name/image_name:version_number
Here the
user_name
is theusername
, that is used to login to thedocker-hub
.image_name
is our desired image name. Theversion_number
is theimage
version number. Instead ofversion_number
we can uselatest
keyword to use the latest version number handled by the docker itself.
We can now run the docker with the tag
docker run user_name/image_name:version_number
Here only the version_number
is the tag itself. The user_name
itself is always the docker id
and image_name
is the project name or the repo name
.
While running our tagged custom
image
we can ignore theversion_number
. It will simply take the latest version.
Hope this will give you an idea of how to build a custom image and the mechanism behind it. To learn more you can check out the official Docker tutorial on how to create a base image.
Feel free to leave any comments for clarification, improvements. Also, you can contact with iXora Solution expert teams for any consultation or coordination from here.
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