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In this step-by-step tutorial, you’ll learn how to build Docker images from scratch using Dockerfile. Perfect for beginners, this video covers everything from Dockerfile basics to real-world examples with Python (Flask) and Java (Spring Boot).
🎬 What You Will Learn:
What a Dockerfile is and why it’s important
Meaning of key Dockerfile keywords (FROM, COPY, RUN, CMD, EXPOSE, VOLUME, ENTRYPOINT)
How Docker images are built in layers for efficiency
Creating Python (Flask) Docker image
Creating Java (Spring Boot) Docker image with Maven
Multi-stage Dockerfiles for smaller, optimized images
✅ Prerequisites:
Docker Desktop / Engine installed
Basic command line knowledge
Java & Python environment
🐍 Python Example – Flask App
Build a Docker image for a Flask app with a multi-stage Dockerfile
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0:00
Hey everyone, welcome back to the
0:01
channel. In today's video, we will learn
0:04
how to build Docker images using Docker
0:06
file from the scratch. We will cover
0:09
what a Docker file is, common keywords
0:12
used in Docker files, layers in Docker
0:14
images, multi-stage builds, and finally
0:18
build two Docker images. One for Python
0:20
app, another one for Java app. I already
0:24
have some sample Python code and app
0:26
code that I will be using during the
0:28
building of these images. A Docker file
0:30
is simply a text file with instructions
0:33
that tell Joker how to build an image.
0:36
It automates everything from installing
0:39
dependencies, copying code, and to
0:42
setting up the environment. Some
0:43
important keywords on the Docker file
0:45
are from it sets the base image. run
0:49
executes the command during the build.
0:52
Copy or add copies the files into the
0:55
container. Workd diir it sets the
0:58
working directory. cmd default command
1:01
executed when a container start. Entry
1:05
point it sets the entry point for the
1:07
container. Expose it specifies the app
1:10
port. Volume mount storage for the
1:14
persistence. Each instruction in a
1:17
docker file creates a new layer. For
1:19
example, from creates the base OS layer.
1:22
Run apt install creates a dependency
1:25
layer. Copy app. py creates the
1:29
application code layer. The best part,
1:33
docker caches these layers and make the
1:36
builds faster. Multi-stage builds help
1:38
optimize image size. Instead of CPing
1:41
extra build tools, we split Docker file
1:44
into a build stage and a runtime stage.
1:48
For example, the first stage builds the
1:51
app with Maven or cred. Second stage
1:54
copies only the final compiled artifact
1:57
into the small image. All right, let's
2:00
move to the demo part where I will build
2:03
these Docker images. If I run ls-l,
2:07
I have two folders. One is for Python
2:10
app, another one is for Java app. Let's
2:12
go to the Python app folder first.
2:19
Inside this Python app folder, I have a
2:22
Python script and requirement.txt.
2:25
I will be using these files while
2:27
building the docker image for this
2:29
Python app. In order to build the docker
2:32
image, first we need to create a file.
2:34
That file name is docker file and d is
2:36
caps here. So let's create a file using
2:40
vi editor.
2:45
Enter into the insert merge and type the
2:48
first keyword here from next specify the
2:53
base image. In our case it would be
2:56
python.
3:01
Hit enter. Type work diir.
3:07
It will set the working directory. In
3:08
our case, it would be / app. Hit enter.
3:12
Next, copy the requirement.txt file
3:16
under this app folder. For that, use
3:18
copy. Specify the file that you want to
3:21
copy. In our case is requirements
3:26
dot txt.
3:29
Next, install the dependencies using
3:32
this requirement.xt file via pip install
3:36
command. For that, first define the word
3:39
run and then specify the command pip
3:44
install - r and then requirement.xt.
3:52
Hit enter. Now copy the app code using
3:55
copy command.
3:58
And in the last we'll define a cmd which
4:02
will start our application. So this will
4:04
be executed whenever a container is
4:07
started using this docker image. Under
4:10
cmd we need to define the exact command
4:13
that we want to execute when we start
4:15
this container using this docker image.
4:21
Type here Python
4:24
and then your app name.
4:29
Save and close the file.
4:32
In order to build this docker image, you
4:34
need to run the command docker
4:38
space build space-en t is for tag. Tag
4:43
means just labeling the docker image. In
4:46
our case, I will set it as python.
4:50
hyphen app
4:53
and dot dot means it will look for this
4:56
docker file inside the current working
4:59
directory. If you hit enter, it will
5:02
start building the docker images. So
5:04
this is completed. Now you can verify
5:08
the docker image.
5:10
Run the command docker images.
5:14
You will see that
5:16
a Python hyphen app docker image of size
5:20
132 MB is created. Let's create a
5:23
multi-stage Docker file for our Python
5:25
app. Multi-stage builds help create much
5:28
smaller images by separating the build
5:30
environment from the final runtime
5:32
image. Let's edit the Docker file.
5:39
Remove these lines.
5:44
For the interest of time, I have already
5:45
prepared the set of sections for this
5:47
multi-stage docker file.
5:50
All right, if you can see, I'm defining
5:53
the first stage as build stage. In the
5:56
build stage, I am pulling this image as
5:59
a builder. I'm setting the work
6:01
directory as app, installing the
6:03
dependencies using the required .txt
6:06
file and running the pip install. After
6:10
that I'm copying the app code to this
6:12
app folder
6:15
and then I'm starting my second stage
6:17
that is runtime stage. For that also I'm
6:20
using the same Python image setting the
6:23
work directory as again as/ app. And now
6:26
I'm copying only the installed packages
6:29
from the builder and updating the
6:32
environment or updating the path
6:34
environment. Once it is done then I'm
6:36
copying the app code and then exposing
6:39
the app on the port 5000 defining the
6:42
volume for our app/ app/ data and then
6:46
running or starting the app using the
6:49
python command. So this cmd whenever
6:53
this container got started using this
6:56
image it will run this command python
6:59
app. py which ultimately starts our
7:01
application. Now save and close the file
7:06
and build the image. For that rerun the
7:10
command docker build space- t and the
7:14
tag name. This time I will specify
7:21
space dot hit enter.
7:25
Docker file creation is also completed
7:28
using this multi-stage. Now verify the
7:31
docker
7:32
image size.
7:37
All right. In order to test this docker
7:39
image, we will start a container. Let me
7:41
clear the screen first.
7:57
Now verify the container. Run docker ps.
8:01
It has started a container using the
8:04
image that we have just built using
8:06
multi-stage. All right, it has started
8:08
this command python space app. py. It
8:11
means our application also got started.
8:14
Now validate this. Open the browser or
8:17
you can also test it from the command
8:19
line. You can simply run the curl
8:21
command here
8:28
enter. You will see the output something
8:31
like this. Hello from Python dockerized
8:33
app. It means our application is started
8:37
successfully in the container using this
8:41
docker image. All right, let's move to
8:44
our second demo where we will be
8:46
building a Docker image for Java app.
8:50
Let's go to our Java app folder.
8:56
You do l you will see our pom.xml and
9:00
our Java app code under the src folder.
9:03
Let's create a docker file here.
9:10
If you see I'm defining two stage. So it
9:12
means I'm using multi-stage docker file.
9:14
Here in stage one I'm saying it's a
9:17
build stage. So for this build stage I'm
9:20
using this maven based image as a
9:22
builder. I'm setting this work directory
9:25
as/shop. I'm copying the pom.xml file
9:28
under this app folder and then copying
9:30
the entire Java code from this src to
9:33
this src folder and then building the
9:35
package using mvn clean package. The
9:39
next stage where we are using a slim
9:42
base image and we call it as slim
9:44
runtime. Here I'm specifying that this
9:48
is the image I would be using it as a
9:50
base image. Work directory is again /
9:53
app. I'm copying the artifacts or the
9:55
jar file that was built in this build
9:59
phase directly from the builders to this
10:02
image and then exposing this application
10:05
on the port 8080. And in order to start
10:08
this application, I'm using entry point
10:11
here. And I'm executing the command java
10:14
space-en jar and then app dot jar. On
10:17
this is executed, it will start our
10:20
application. All right. Save and close
10:22
this file.
10:24
Now run the docker build command in
10:27
order to build this docker image.
10:32
The tag name is Java app and then doge.
10:37
Hit enter. Sorry, typo. Let's correct
10:40
it. It's build.
10:45
Okay, the output confirms that docker
10:46
image has been built successfully. Let's
10:49
verify it and the command
10:52
docker images. Our Java based Docker
10:57
image is created. All right, let's start
11:01
a container using this docker image and
11:04
let's validate whether our application
11:06
is accessible or not. We clear the
11:09
screen first
11:11
and the command docker run-d
11:15
[Music]
11:21
name is
11:23
Java - app. Hit enter. run docker ps
11:29
you will see one container got started
11:32
with the name this one it is using this
11:35
image that we have just built and it is
11:38
executing the command java space-en jar
11:42
space app dot jar so it will start our
11:45
application it's the same command that
11:47
we have defined in the entry point uh
11:49
keyword in the docker file let's try to
11:52
access this application run the command
11:54
curl
11:58
All right, we we are getting the
12:00
response from application. This confirms
12:02
that our application is accessible using
12:06
this container which is started using
12:08
this docker image. That's all from this
12:11
video tutorial. I hope you have found it
12:13
useful and informative. Do not forget to
12:15
like, share and subscribe for more
12:17
DevOps tutorials. Thank you. Bye. Have a
12:19
nice day. See you in the next one.
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