How To Build Docker Image For Beginners? (Updated 2023)

Are you looking for an in-depth guide on how to build a Docker image step by step? Read on.

Docker is a software tool that enables the creation, distribution, and operation of lightweight application containers.

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For those looking for a basic understanding of Docker, the Docker explained blog is an excellent resource to refer to.

So, let’s get started quickly.

What Is Dockerfile?

Dockerfile is the fundamental component required to create a Docker image. This is a straightforward text file containing directions and parameters, and Docker can automatically generate images by interpreting the instructions outlined within a Docker file.

In a Dockerfile, each left-hand side component represents an instruction, while each right-hand side component represents an argument corresponding to that instruction.

It is important to note that the filename for the Dockerfile should be “Dockerfile” without any file extension.

Listed below are crucial Dockerfile commands alongside their corresponding definitions for reference:

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How To Build Docker Image Using Dockerfile

Here are the simple and detailed steps to build a Docker Image using the Dockerfile.

Prerequisites:

Docker: Ensure you have Docker installed on your system. You can download and install Docker from the official Docker website.

Step 1: Create a Dockerfile:

The Dockerfile is a text file that contains instructions for building a Docker image. It specifies the base image, environment variables, application code, dependencies, and how to configure the image. Create a file named Dockerfile in the root directory of your project.

Here’s a basic Dockerfile example for a Python application:

# Use an official Python runtime as the base image
FROM python:3.8

# Set environment variables
ENV APP_HOME /app
WORKDIR $APP_HOME

# Copy the application code into the image
COPY . $APP_HOME

# Install application dependencies
RUN pip install -r requirements.txt

# Expose a port if your application listens on a specific port
EXPOSE 8080

# Define the command to run the application
CMD ["python", "app.py"]

Now, you need to customize the Dockerfile to match the specific requirements of your application.

Step 2: Organize Project Files:

Place all the necessary files for your application in the project directory. In the example above, the requirements.txt file contains Python dependencies and app.py is the main application script.

Make sure the Dockerfile and these files are in the same directory.

Step 3: Build the Docker Image:

Open a terminal and navigate to the directory containing the Dockerfile. Use the docker build Command to build the Docker image. Provide a name and tag for the image. For example:

docker build -t my-python-app:1.0 .

• -t specifies the name and tag for the image.
• my-python-app Is the name of the image.
• 1.0 is the tag (version) of the image.
• . indicates the build context (the current directory where the Dockerfile and project files are located).

Docker will execute the instructions in the Dockerfile and create a new image. This process may take some time, depending on the complexity of your application and the image’s size.

Step 4: Verify the Image:

To verify that the image was built successfully, you can use the docker images Command to list all the images on your system:

docker images

You should see your newly created image listed.

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Step 5: Run a Container from the Image:

Once you have built the image, you can create and run containers. Use the docker run Command to start a container based on your image:

docker run -p 8080:8080 my-python-app:1.0

• -p Maps a port from the host to the container (if your application listens on a specific port).
• my-python-app:1.0 Specifies the image and tag to use.

Step 6: Access Your Application:

If your application exposes a web service on port 8080, you can access it in your web browser by navigating to http://localhost:8080 (or the host’s IP address).

Adjust the port number and address based on your application’s configuration.

WOW! You’ve successfully built a Docker image & created a running container from it.

As you know, the Docker simplifies the process of packaging, distributing, and running applications in isolated environments, making it easier to manage software deployments.

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What Are Some Dockerfile Best Practices?

Below, I have mentioned some of the best Dockerfile practices you must follow.

1. Using a .dockerignore file to exclude unnecessary files & directories which can improve build performance.
2. Only use trusted base images, and update them periodically to ensure your images remain secure.
3. Consolidate instructions within the Dockerfile to minimize the number of layers & improve the build’s performance.
4. You can run the container as a Non-Root User to avoid potential security breaches.
5. Keep the image size small to reduce the attack surface and minimize the deployment time. Use minimal images and avoid installing unnecessary tools in your image.
6. Use specific tags over the latest tag to prevent breaking changes over time.
7. Avoid multiple RUN commands, as they generate multiple cacheable layers that can impact build efficiency.
8. Do not share or copy sensitive information or application credentials in the Dockerfile. If necessary, add them to .dockerignore instead.
9. Use EXPOSE and ENV commands as late as possible in the Dockerfile.
10. Consider using a linter, such as hadolint, to check for common issues and best practices in your Dockerfile.
11. Use a single process per container for easier management and monitoring and to keep the containers lightweight.
12. Utilize multi-stage builds to create smaller and more efficient images.

What Are The Possible Docker Build Issues?

1. Syntax errors or invalid arguments in the Dockerfile can cause the docker build command to fail with an error message. Correcting the syntax will typically resolve this issue.
2. When using the docker run command, it is advisable to assign a name to the container to avoid potential problems that may arise when Docker automatically gives a name.
3. Occasionally, the error message “Bind for 0.0.0.0.:8080 failed: port is already allocated” may appear, indicating that another software or service is using the specified ports. You can check for any listening ports using commands such as netstat or ss, and either use a different port or stop the conflicting service.
4. Another error that may occur is “Failed to download package,” which can arise due to various factors, such as a lack of internet access for the container or dependency issues. Troubleshooting these underlying causes can help resolve this error 💻.

Docker Image Registries

I recommend you select verified official base images for your application, as discussed in Step 1.

Many publicly available container registries offer officially verified base and application images, as listed in the following table.✅

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Docker Image Vs. Containers

A Docker image is an executable package that contains all the necessary components to run an application, including its code, dependencies, tools, and other files.

When analyzed, you can see it is similar to a golden image in a virtual machine. The image comprises multiple read-only layers stacked on top of each other.

On the other hand, a Docker container is a running instance of a Docker image. Like virtual machines, containers are created from images. When a container is created from an image, it adds a writable layer on top of its read-only layers.

The main difference between an image and a container is that an image is read-only, while a container has a writable layer. This means that multiple containers can run from the same image, with each container having its writable layer separate from the others.

Containers can be deleted without affecting the underlying images. However, an image cannot run without a container. We can create multiple containers from the same image, each with its unique data and state.

Conclusion: Build Docker Image

In this article, I have covered everything on how to build a Docker Image and run an application as a Docker container using a Docker file with some best practices for writing a Dockerfile.

A strong understanding of Docker’s best practices is important for DevOps engineers when implementing them in a project.💻

Furthermore, understanding the process of building container images is essential for learning Kubernetes.

Frequently Asked Questions