Docker Image vs Container: Understanding the Lifecycle & Key Differences

Docker is an open-source platform that helps streamline work for developers. It gives teams a practical way to build, move, and run applications with containerization. Over time, it has become one of those tools you expect to find in any modern software project. Deployments go faster, and the whole system runs smoothly.

The changes in how we build, ship, and manage applications since Docker came out are huge. Many beginners struggle to distinguish between a docker image and a docker container.

Let’s break that down together, talk through how these pieces connect, and take a look at what each one does during the container lifecycle when it’s time to get your app running.

If you’re looking to streamline development and deployment pipelines, explore our devOps services for docker and CI/CD

Docker Images vs. Containers Flowchart

Prerequisites 

Basic Understanding of Virtualization

Picture virtualization as running several “computers” inside one physical machine. It’s a helpful starting point. docker containers are similar, just lighter and less resource-hungry. Instead of spinning up full virtual machines, containers share parts of the machine’s system to operate apps independently.

Familiarity with Command-Line Interfaces

You’ll need to use the terminal, a black window where you type Docker container commands. If you know how to switch folders or run a basic script, you’re already set to move through the process more easily.

Docker Installed

To follow along, docker needs to be set up on your device. It’s available for Windows, Mac, and Linux. You can grab the installer from Docker’s official site.

Basic Knowledge of Containers

Knowing what a container is always helps. Think of it as a lightweight, self-contained package for apps. If you’ve bumped into Kubernetes before, you’re halfway there. Kubernetes exists to manage lots of containers across their lifecycle states.

You can also hire docker consultants for container strategy and lifecycle management to optimize your workflows

What is a Docker Image?

A docker image acts like a starter kit for software. It’s a lightweight, standalone file that has everything an app needs: the application code, the required dependencies like libraries, runtime, system tools, frameworks, plus any custom settings packed inside.

Once you build an image, it’s read-only. You can’t change it without building a new one. In practice, it’s your template,something you “stamp out” docker containers from, over and over.

Key Characteristics of Docker Images

• Immutable: Once built, an image remains unchanged. Any modification requires creating a new image.
• Portable: Can be shared and deployed across different environments.
• Layered Structure: Built using a layered file system that optimizes storage and reuses common layers.
• Versioned: Each image can be tagged with different versions (e.g., nginx:1.21, python:3.9).
• Reusable: You can share and reuse images across different environments. They are typically stored in a Docker registry like Docker Hub, where you can pull public images or push your own.

What is a Docker Container?

A Docker container comes to life when an image runs. Think of the image as a recipe, and the container as the chef working live in its own kitchen.

A container starts as an image, but once it’s running, it becomes a secluded space for your app. Each container runs independently. It happens when sharing the host’s kernel; this keeps things light and quick.

When you launch an app in a container, Docker creates a sandboxed environment where everything operates separately from the rest of your system. Containers are flexible, as they include a writable layer. So, data can change how your app runs and adapt on the fly throughout the container lifecycle.

Key Characteristics of Docker Containers

Ephemeral by Default

Stop or delete a container, and you lose what’s inside, but the image remains untouched.

Isolated

Every container gets its own space to run, but you can let them talk to each other if that’s needed.

Lightweight

Since they share the host’s kernel, containers use a lot less overhead than old-school virtual machines.

Configurable

Change containers with different environment settings, adjust their networks, or attach storage; each container can be set up the way you need.

Learn more about docker container monitoring with prometheus and grafana for real-time insights

Relationship Between Docker Images and Containers

Docker Images as Templates

A Docker image is a read-only template that needs code, libraries, dependencies, and environment variables. It acts as a blueprint for creating containers.

Containers as Live Instances

When you run an image with the docker run command, it creates a container. It runs the app from that image and maintains its own isolated environment.

Multiple Containers from One Image

You can launch many containers from one image. Each container runs independently, even though they share the same base image. This runs identical apps with different configurations.

Additional Details

Layered Architecture

Docker builds images in layers. Each layer records a change, such as installing a package or adding a file. These layers remain cached, so Docker can reuse them. This reduces storage use and speeds up image build and push/pull processes. When a container starts, it adds a writable layer on top so changes can occur while it runs.

Immutability of Images

Once you build an image, you cannot change it directly. To modify it, you need to create a new one. You can do this by adjusting a container and committing changes to the dockerfile before rebuilding.

Reusability and Efficiency

Thanks to the layered structure, docker images are highly efficient. Shared layers minimize redundancy, speed up deployment, and support multiple containers across different lifecycle stages.

For a deeper dive into automation, explore our detailed guide on CI/CD pipeline with docker and aws.

Docker Installation Steps for Containers and Images

Step 1: Update Your System First

Make sure your package index is up to date. Open your terminal and run

sudo apt-get updateCode language: JavaScript (javascript)

Step 2: Install Required Packages

Docker installation requires some dependencies like ca-certificates, curl, and GnuPG. Install them with

sudo apt-get install -y ca-certificates curl gnupgCode language: JavaScript (javascript)

Step 3: Create a Keyrings Directory

Docker recommends storing its GPG key in a dedicated keyring directory. Let’s create it

sudo install -m 0755 -d /etc/apt/keyrings

Step 4: Add Docker’s Official GPG Key

Next, download and save Docker’s official GPG key

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | \Code language: JavaScript (javascript)

sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg

This step ensures the packages you install stay authentic and safe.

Step 5: Set Permissions on the GPG Key

Make the key readable by the apt system:

Sudo chmod a+r /etc/apt/keyrings/docker.gpg

Step 6: Update Your Package Index Again

After adding the Docker repository, update the package index again:

sudo apt-get updateCode language: JavaScript (javascript)

Step 7: Install Docker Engine & Plugins

 sudo apt-get install -y \
    docker-ce \
    docker-ce-cli \
    containerd.io \
    docker-buildx-plugin \
    docker-compose-pluginCode language: JavaScript (javascript)

This installs everything you need to build docker images and manage container lifecycles.

Step 8: Add Your User to the Docker Group

Docker requires sudo for commands by default. If you want to run Docker as a regular user, add your user to the Docker group.

sudo usermod -aG docker ubuntu

Important: You’ll need to log out and log back in for the new group membership to take effect!

Step 9: Fix Common Docker Installation Issues

If you find any error while installing it, there should be sources.list.d missing, so you want to create that file using the below command 

sudo mkdir /etc/apt/sources.list.dCode language: PHP (php)

sudo chmod 666 /var/run/docker.sockCode language: JavaScript (javascript)

Step 10: Test Your Docker Installation and Running Containers

Finally, test that Docker is working:

docker ps

If you see an empty list of containers without errors, congratulations. Docker is installed and ready to use!  To strengthen your DevOps security posture, check out how DevSecOps with SonarQube and OWASP helps mitigate risks early.

Simple Example: Docker Image Build and Container Lifecycle

Step 1: Pull the Docker Image

docker pull python:3.11Code language: CSS (css)

Step 2: Run a Container from an Image

docker run python:3.11 python --versionCode language: CSS (css)

Python 3.11.xCode language: CSS (css)

Docker Compose Example with PostgreSQL

Create a YAML file named docker-compose-postgresql-16.yml.

version: '3.8'
services:
  db:
    image: postgres:16
    restart: always
    environment:
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: mobisoft
      POSTGRES_DB: your_database_name
    ports:
      - '5433:5432'
    volumes:
      - $HOME/myapp/postgres_16:/var/lib/postgresql/data
    deploy:
      resources:
        limits:
          memory: 512MCode language: PHP (php)

Step 1:  Docker Compose File for PostgreSQL Lifecycle Management

docker compose -f docker-compose-postgresql-16.yml  --compatibility up Code language: CSS (css)

Step 2: Check Docker Images and Running Containers

docker images

Step 3: Check Docker Images and Running Containers

docker ps

Step 4: Access a Running PostgreSQL Container

docker exec -it docker_postgres_1 psql -U postgres 

Postgres Service file

[Unit]
Description=postgresqlService
Requires=postgresql16.service
After=docker.service
[Service]
Restart=always
User=phapalnavnath
Group=docker

# Shutdown container (if running) when unit is stopped

ExecStartPre=docker compose -f /home/phapalnavnath/docker/docker-compose-postgresql-16.yml --compatibility down -v

# Start container when unit is started

ExecStart=docker compose -f /home/phapalnavnath/docker/docker-compose-postgresql-16.yml --compatibility up

# Stop container when unit is stopped

ExecStop=docker compose -f /home/phapalnavnath/docker//docker-compose-mysql8.yml --compatibility down -v
[Install]
WantedBy=multi-user.targetCode language: JavaScript (javascript)

# Create a symlink if the file was originally outside /etc/systemd/system

sudo ln -s /home/phapalnavnath/docker/postgresql16.service

# Reload systemd so it recognizes the new service

sudo systemctl enable postgresql16.serviceCode language: CSS (css)

# Enable the service to auto-start at boot

sudo systemctl daemon-reload

# Start the service now

sudo systemctl status postgresql16.serviceCode language: CSS (css)

docker ps

docker exec -it docker_db_1 psql -U postgres 

Benefits

• Auto-recovery: Systemd restarts PostgreSQL if it crashes.
• Boot time: The system starts it automatically when the machine boots.

Docker Compose Example with MySQL Containers

Step 1: Create a MySQL Docker Compose File

version: '3.8'
services:
  mysql:
    image: mysql:8.0
    container_name: mysql-db
    restart: always
    environment:
      MYSQL_ROOT_PASSWORD: mobisoft
      MYSQL_DATABASE: mydatabase
      MYSQL_USER: myuser
      MYSQL_PASSWORD: userpassword
    ports:
      - '3307:3306'
  
  volumes:
      - mysqldata:/var/lib/mysql
    deploy:
      resources:
        limits:
          memory: 512M
volumes:
  mysqldata:/var/lib/mysqlCode language: JavaScript (javascript)

Step 2: Start the containers

docker compose -f docker-compose-mysql.yml --compatibility up Code language: CSS (css)

Step 3: Docker images

Step 4: Check running containers

docker ps

Step 5:  Access the MySQL client running inside a Docker container.

docker exec -it 677f4fa66b86 mysql -u root -p

MySQL Service file

[Unit]
Description=mysqlService
Requires=mysql.service
After=docker.service
[Service]
Restart=always
User=phapalnavnath
Group=docker

# Shutdown container (if running) when unit is stopped

ExecStartPre=docker compose -f /home/phapalnavnath/docker/mysql/docker-compose-mysql8.yml --compatibility down -v

# Start container when unit is started

ExecStart=docker compose -f /home/phapalnavnath/docker/docker-compose-mysql8.yml --compatibility up

# Stop container when unit is stopped

ExecStop=docker compose -f /home/phapalnavnath/docker//docker-compose-mysql8.yml --compatibility down -v
[Install]
WantedBy=multi-user.targetCode language: JavaScript (javascript)

sudo ln -s /home/phapalnavnath/docker/mysql.service

sudo systemctl enable mysql.service

sudo systemctl daemon-reload

sudo systemctl status mysql.service

docker ps

docker exec -it docker_mysql_1 mysql -u root -p

Benefits

• Auto-recovery: If PostgreSQL crashes, systemd will restart it
• Boot time: Starts automatically when the machine boots

Docker Compose Example: Running a Multi-Container Application

Step 1: Create a Docker Compose File for Multiple Services

version: "2.1"

services:
  yelb-ui:
    image: mreferre/yelb-ui:0.10
    depends_on:
      - yelb-appserver
    ports:
      - "8080:80"
    environment:
      - UI_ENV=test
    mem_limit: 512m

  yelb-appserver:
    image: mreferre/yelb-appserver:0.7
    depends_on:
      - redis-server
      - yelb-db
    ports:
      - "4567:4567"
    environment:
      - RACK_ENV=test
    mem_limit: 512m

 
 redis-server:
    image: redis:4.0.2
    ports:
      - "6379:6379"
    mem_limit: 512m

  yelb-db:
    image: mreferre/yelb-db:0.6
    ports:
      - "5432:5432"
    mem_limit: 512m
Code language: JavaScript (javascript)

Step 2: Start All Containers Together

docker compose -f docker-compose.yml --compatibility up Code language: CSS (css)

Step  3: Check Running Containers and Lifecycle States

docker ps

Step 4: Access the Application

http://localhost:8080

Key Differences Between Docker Images and Containers

Conclusion

Understanding the difference between Docker images and containers is crucial for modern development. Think of an image as the recipe and the container as the dish. Images define the blueprint, while containers represent the runtime state and lifecycle.

Using both together lets you build scalable applications, manage container lifecycle states, and optimize deployments across environments. For CTOs, CROs, and engineering leaders, mastering this distinction ensures smoother DevOps pipelines, better scalability, and efficient resource management. To scale your engineering capabilities, you can hire devOps engineers for docker and cloud automation

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