Docker Images Explained: What You Should Know
Before containerization, deploying applications typically involved setting up dedicated servers or virtual machines. Virtual machines emulate entire hardware systems, including their guest operating systems, on top of a host machine, which makes them heavy and resource-intensive. Setting up a virtual machine requires installing the OS, configuring the network, and ensuring compatibility with the target environment. This process consumed significant time and required skilled manpower.
Each virtual machine was isolated, but came at the cost of high overhead because multiple operating systems ran simultaneously on the same hardware. Applications deployed on VMs also faced challenges with portability and consistency. An application that worked on one VM might fail on another due to differences in environment configurations or installed dependencies.
Sharing these environments was difficult. Developers often resorted to sharing VM images, which were large files, slowing down collaboration. Updating these environments also required significant effort as changes in dependencies or configurations meant rebuilding and redeploying VMs.
This made the development lifecycle slow, costly, and error-prone.
Containers emerged as a lightweight alternative to virtual machines, revolutionizing how developers build and deploy applications. Instead of bundling an entire OS, containers share the host operating system’s kernel but run isolated processes within their own user spaces.
This architecture drastically reduces overhead. Containers start much faster than VMs, consume less disk space, and use fewer resources. This efficiency enables developers to run multiple containers simultaneously on a single host without performance degradation.
Because containers encapsulate the application and its dependencies, they guarantee that the application will run consistently across different environments — be it a developer’s laptop, a test server, or a cloud platform. This solves the “it works on my machine” problem.
Containers also simplify continuous integration and continuous deployment (CI/CD) pipelines. Developers can package an application into a container image, test it in a staging environment, and deploy the same image to production without changes.
Docker is the most popular container platform that standardizes the process of creating, distributing, and running containers. Docker introduced a format for container images and tools for building and running them.
Docker Images are central to this ecosystem. They are the portable, versioned files that contain everything an application needs to run. When you want to launch an application, you create a Docker Container from an image.
Docker’s layered image system optimizes storage and bandwidth. Common layers (such as a base OS or runtime) are shared between images and cached locally, avoiding duplication.
Docker Hub is the official public registry where users can find and share pre-built images. This encourages reuse and accelerates development by leveraging existing images.
Each Docker Image is made up of a series of read-only layers. These layers represent incremental changes made by each instruction in a Dockerfile.
For example, starting from an empty base, you might add a layer for the base OS, then another for installing Nginx, then another for copying application files. Each layer stores only the differences from the previous layer.
This layering brings several advantages:
When a container runs, Docker adds a thin writable layer on top of these image layers. This allows the container to write data during execution without modifying the original image.
A Dockerfile is a simple text file containing instructions that define how to build a Docker Image. It specifies a base image and a sequence of commands that configure the environment.
The most common instructions in a Dockerfile include:
Using Dockerfiles ensures reproducibility. Any developer can build the same image on any machine using the Dockerfile, ensuring consistency across development and production environments.
Let’s explore building a Docker Image from scratch for a simple Node.js web application.
Step 1: Define the Base Image
We start by choosing a base image that provides the runtime environment, such as an official Node.js image.
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FROM node:14
Step 2: Set the Working Directory
Specify a directory inside the container where the application files will reside.
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WORKDIR /app
Step 3: Copy Application Files
Copy the application source code and package files from the host machine into the container.
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COPY package.json package-lock.json ./
COPY . .
Step 4: Install Dependencies
Run the command to install Node.js dependencies.
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RUN npm install
Step 5: Expose Application Port
Let Docker know which port the app listens on.
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EXPOSE 3000
Step 6: Define the Startup Command
Specify the command to run the app.
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CMD [“node”, “server.js”]
This Dockerfile builds an image capable of running the Node.js application with all dependencies included.
Docker Images can be obtained in two ways: by building custom images locally using Dockerfiles or by pulling pre-built images from registries.
The docker pull command downloads images from Docker registries such as Docker Hub. When pulling an image, if the image already exists locally, Docker checks for updates and downloads only layers that have changed.
For example, to pull the latest Ubuntu image:
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docker pull ubuntu: latest
The latest tag indicates the most recent version, but specific versions or tags can be specified.
After pulling, you can list all local images using:
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docker images
This command displays the repository name, tag, image ID, creation date, and size.
Tags in Docker Images serve as identifiers to differentiate between versions or variants of the same image. Tags allow you to specify which version of an image you want to use.
For example, the nginx image has tags such as latest, alpine, or specific version numbers like 1.21.6. Using tags helps ensure consistency and control over the environment your container runs.
If no tag is specified, Docker defaults to using the latest tag.
Docker uses a layered filesystem and content-addressable storage. Each layer is identified by a cryptographic hash, which means identical layers share the same identifier and storage.
When you build or pull images, Docker checks if the layer already exists locally. If it does, it uses the cached version, saving bandwidth and speeding up the process.
This caching is particularly useful during image builds. If the earlier steps in a Dockerfile remain unchanged, Docker reuses cached layers rather than rebuilding from scratch.
Docker Images contain all necessary files and libraries to run an application, but they can also introduce security risks if not managed properly.
It’s important to:
By following best practices, you can maintain secure container environments.
Building Docker Images involves creating a Dockerfile with a sequence of instructions that define the environment and application setup. When you run the Docker build command, Docker reads the Dockerfile, executes each instruction, and creates intermediate image layers for each step. These layers are then combined into a final image.
An effective Dockerfile follows best practices to optimize image size, build speed, and maintainability. Here are some important guidelines:
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FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt.
RUN pip install –no-cache-dir -r requirements.txt
COPY . .
EXPOSE 5000
CMD [“python”, “app.py”]
In this example, the image uses a minimal Python base, installs dependencies without caching, and copies only needed files.
To build an image from a Dockerfile, navigate to the directory containing the Dockerfile and run:
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docker build -t image_name: ta
Docker reads the Dockerfile, executes each instruction, and creates the image. The resulting image can then be listed using docker images.
The build context includes all files and folders in the directory specified during the build command. Docker sends this context to the Docker daemon for use during the image build.
Including unnecessary files in the build context can slow down builds and increase image size. Using a .dockerignore file allows you to exclude files such as documentation, local config files, or .git directories.
Example .dockerignore:
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.git
node_modules
*.log
This ensures only essential files are sent to the daemon.
Tags help organize and manage versions of images. It’s good practice to tag images with semantic versions or meaningful labels.
Example:
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docker build -t myapp:1.0.0.
Docker build -t myapp: latest.
You can push specific tags to registries and pull exact versions as needed.
To clean up disk space or remove unused images, use:
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docker rmi image_name:tag
If an image has containers depending on it, Docker will warn you. You may have to remove those containers first.
To get detailed metadata about an image, run:
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docker inspect image_name:tag
This returns JSON output containing configuration details such as environment variables, entry points, layers, and network settings.
Registries are centralized repositories to store and distribute Docker Images. They provide:
After building a local image, you can upload it to a registry for sharing or deployment.
Steps to push:
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docker tag myapp: latest myregistry.com/myapp:latest
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docker login myregistry.com
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docker push myregistry.com/myapp:latest
This makes the image available for other users or deployment environments to pull.
You can pull images using:
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docker pull image_name:tag
If no tag is specified, the latest tag is used by default.
To ensure the authenticity of images, Docker supports content trust and image signing. This prevents tampered or untrusted images from being deployed.
Docker Images are static templates. Containers are the running instances created from these images.
To run a container from an image:
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docker run -d -p 8080:80 mynginx: latest
Containers have writable layers on top of the image layers. Changes made inside a container do not affect the underlying image.
For persistent storage beyond the container lifecycle, Docker volumes or bind mounts are used. Volumes allow data to persist even if containers are deleted.
Containers can be connected to networks to communicate with each other. Docker supports various networking modes: bridge, host, overlay, and macvlan.
This enables microservices architectures where multiple containers interact over well-defined network interfaces.
Building efficient Docker Images is crucial for fast deployments and minimal resource consumption.
Multi-stage builds let you use multiple FROM statements in a Dockerfile. The final image only contains files copied from the previous stages, keeping it lightweight.
Example:
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FROM golang:1.17 as builder
WORKDIR /app
COPY . .
RUN go build -o myapp
FROM alpine: latest
COPY– from=builder /app/myapp /usr/local/bin/myapp
CMD [“myapp”]
This builds the Go app in a large build environment but ships a minimal Alpine-based runtime image.
Ordering instructions in Dockerfiles to leverage the build cache improves build speed. Changes to files copied earlier invalidate more layers.
Grouping related commands and minimizing file changes reduces cache invalidation.
Docker Images are constructed as a series of layers. Each instruction in a Dockerfile creates a new read-only layer, stacked on top of the previous ones. These layers improve build efficiency and image sharing.
When you build an image, Docker reuses layers from previous builds if the corresponding instructions haven’t changed. This layered architecture allows for:
Each layer contains filesystem changes like added files, modifications, or deletions. Layers are immutable once created.
Since layers are stacked, each adds to the total image size. Overly large images can cause slower deployments and increased storage costs.
Key points to reduce layer size:
For example, instead of:
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RUN apt-get update
RUN apt-get install -y package
RUN apt-get clean
Use:
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RUN apt-get update && apt-get install -y package && apt-get clean
This creates a single layer rather than three.
Each image layer has associated metadata such as:
This metadata helps Docker optimize builds and manage the image lifecycle.
You can inspect this data with:
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docker history image_name:tag
This shows the layer-by-layer breakdown and the commands used to build each layer.
Security is a critical aspect of using Docker Images, especially when deploying applications in production.
Docker provides integrated scanning capabilities that check images against known vulnerability databases.
Example command:
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docker scan myapp: latest
This will report any issues, their severity, and remediation recommendations.
Image signing adds a layer of trust by cryptographically verifying image authorship.
Docker Content Trust (DCT) allows you to sign images before pushing to a registry and verify signatures before pulling.
To enable:
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export DOCKER_CONTENT_TRUST=1
This ensures only signed images are used.
For enterprises or projects with proprietary code, private registries provide secure image storage.
You can deploy your registry server using the official Docker Registry image:
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docker run -d -p 5000:5000 –restart=always –name registry registry:2
This runs a local registry on port 5000. Images can be tagged and pushed to this registry:
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docker tag myapp localhost:5000/myapp
docker push localhost:5000/myapp
Private registries support access control, encrypted communication (TLS), and storage backends.
DTR is an enterprise-grade registry solution with additional features like vulnerability scanning, role-based access control, and image signing.
Registries often accumulate many images and tags. Implementing cleanup policies prevents storage bloat:
Automated builds improve development efficiency by rebuilding images on code changes.
Common approaches:
A typical pipeline includes:
To inspect a container created from an image:
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docker exec -it container_id /bin/bash
You can explore the filesystem, logs, and processes inside the container.
BuildKit is a newer backend for Docker builds that enables:
Enable BuildKit with:
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DOCKER_BUILDKIT=1 docker build.
A Dockerfile is a simple text file that contains a set of instructions for Docker to build a Docker image. These instructions can include setting up an operating system, installing dependencies, copying application files, setting environment variables, and defining commands to run when the container starts.
Each instruction in the Dockerfile creates a new layer in the resulting Docker image, and Docker uses these layers to optimize the build process. Dockerfiles help ensure that applications are packaged consistently and reproducibly, which is one of the primary advantages of containerization.
Dockerfiles are crucial because they automate the process of setting up an environment for an application. By using a Dockerfile, developers and DevOps teams can ensure that the application runs the same way across various environments—be it on a local developer machine, in a test environment, or production.
The benefits of using Dockerfiles include:
Dockerfiles contain a series of instructions that tell Docker how to set up the container environment. Each instruction creates a new layer in the image, and these layers are cached to improve build efficiency. Let’s go over some of the most important Dockerfile instructions:
The FROM instruction is the first line in a Dockerfile and specifies the base image from which the new image will be built. This base image can be any Docker image available on Docker Hub or a custom image from a private registry.
The FROM instruction is followed by the name of the image and, optionally, a tag that specifies a particular version of the image. For example:
FROM node:14
This instruction tells Docker to use the official Node.js image, version 14, as the starting point for the new image. The FROM instruction is essential because it determines the environment in which the application will run.
The RUN instruction is used to execute commands inside the container while building the image. It is commonly used to install software packages, update the operating system, or configure the environment.
For example:
RUN apt-get update && apt-get install -y curl
In this example, the RUN instruction updates the system package list and installs the curl package. Each RUN instruction creates a new layer in the image that includes the results of the command.
The COPY instruction is used to copy files or directories from the host system (the machine building the image) to the container’s filesystem.
For example:
COPY. /app
This command copies the current directory on the host machine (.) to the /app directory inside the container. The COPY instruction is often used to include the application code or configuration files in the container.
The ADD instruction works similarly to the COPY instruction, but it includes additional features. For instance, ADD can handle compressed files (like .tar, .tar.gz) and automatically extract them during the copy process.
For example:
ADD archive.tar.gz /app
This command extracts the contents of archive.tar.gz into the /app directory in the container. ADD should be used when these additional features are needed, but in most cases, COPY is sufficient and preferred due to its simplicity.
The EXPOSE instruction is used to document which ports the container will listen on at runtime. It does not publish the ports but merely acts as a reminder for developers or operations teams.
For example:
EXPOSE 80
This instruction informs Docker that the container will listen on port 80. While this does not make the port accessible externally, you can map this internal port to an external port when running the container with the p option.
The CMD instruction specifies the default command that will be executed when the container starts. The CMD instruction can be overridden by providing a command when running the container with docker run.
For example:
CMD [“node”, “server.js”]
This example tells Docker to run the server.js file with Node.js when the container starts. If no command is specified when running the container, this CMD will be used.
While the CMD instruction specifies the default command, ENTRYPOINT is used to set the executable that will run when the container starts. ENTRYPOINT is often used to configure the container as a specific command.
For example:
ENTRYPOINT [“python”]
CMD [“app.py”]
In this case, the ENTRYPOINT is set to Python, and the CMD provides the argument app.py. When the container starts, it will run the python app.py. If additional arguments are provided at runtime, they will be passed to the ENTRYPOINT command.
The ENV instruction sets environment variables inside the container. Environment variables can be used to configure the behavior of the application at runtime.
For example:
ENV NODE_ENV=production
This sets the environment variable NODE_ENV to production, which can be accessed within the container by the application.
The WORKDIR instruction sets the working directory inside the container for any subsequent instructions that work with the filesystem, such as RUN, COPY, or ADD.
For example:
WORKDIR /app
This instruction sets the working directory to /app inside the container. If the directory does not exist, Docker will create it.
Let’s take a look at an example Dockerfile for a Node.js web application:
# Step 1: Define the base image
FROM node:14
# Step 2: Set the working directory inside the container
WORKDIR /app
# Step 3: Copy the package files
COPY package.json package-lock.json ./
# Step 4: Install dependencies
RUN npm install
# Step 5: Copy the application code
COPY . .
# Step 6: Expose the port the application will run on
EXPOSE 3000
# Step 7: Define the startup command
CMD [“node”, “server.js”]
Once you have created a Dockerfile, you can build the Docker image using the docker build command. This command reads the Dockerfile and executes the instructions step by step, creating layers along the way.
For example:
Docker build -t myapp: latest.
This command tells Docker to build the image from the Dockerfile in the current directory (indicated by the dot) and tag it as myapp: latest.
While Dockerfiles provide a powerful mechanism for creating consistent and reproducible container images, it’s important to follow best practices to ensure that your Dockerfiles are efficient, secure, and maintainable.
Start with minimal base images, such as Alpine, to reduce the final image size. Smaller images mean faster builds and less resource consumption. For example:
FROM node:14-alpine
Each instruction in a Dockerfile creates a new layer, so it’s essential to minimize the number of layers to improve build speed and reduce image size. You can combine multiple instructions into a single RUN command using &&.
For example:
RUN apt-get update && apt-get install -y curl && apt-get clean
When installing packages or dependencies, it’s a good practice to clean up any unnecessary files to keep the image small. For example, remove cache files created during package installation:
RUN apt-get update && apt-get install -y curl && apt-get clean
Avoid hardcoding sensitive data, such as passwords or API keys, directly in the Dockerfile. Instead, use environment variables or external configuration files to inject secrets into the container at runtime.
Use .dockerignore files to exclude unnecessary files and directories from being copied into the image. This helps reduce the size of the build context and ensures that only essential files are included in the image.
Example .dockerignore:
.git
node_modules
*.log
Dockerfiles are an essential part of Docker’s containerization process, enabling developers to automate the creation of consistent, reproducible images for their applications. Understanding the key instructions and following best practices can help you write efficient and secure Dockerfiles that improve your development and deployment workflows.
By mastering Dockerfiles, you can leverage the power of containers to streamline application development, enhance portability, and ensure consistency across different environments.
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