Ubuntu is the most common Linux distribution for running Docker — whether on a local dev machine, a CI runner, or an EC2 instance. The install process is the same in all three cases.

Update the System

sudo apt update && sudo apt upgrade -y

Install Required Packages

sudo apt install -y apt-transport-https ca-certificates curl software-properties-common

Add Docker’s Official GPG Key

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg

Add the Docker Repository

echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] \
  https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" \
  | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

Install Docker Engine

sudo apt update
sudo apt install -y docker-ce docker-ce-cli containerd.io

Start Docker and Enable at Boot

sudo systemctl start docker
sudo systemctl enable docker

By default, Docker commands require sudo. Add your user to the docker group to remove that requirement:

sudo usermod -aG docker $USER

Log out and back in (or run newgrp docker) for the group change to take effect.

Verify the Installation

docker run hello-world

You should see a “Hello from Docker!” confirmation message.

Install Docker Compose

Docker Compose is distributed as a standalone binary:

sudo curl -L "https://github.com/docker/compose/releases/download/v2.21.0/docker-compose-$(uname -s)-$(uname -m)" \
  -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
docker-compose --version

Practical Example: Containerising a Python ML Script

A common use case: you have a Python script that runs on EC2 and you want to package it so it runs identically everywhere.

Project structure:

my-pipeline/
├── Dockerfile
├── requirements.txt
└── process.py

requirements.txt:

pandas
boto3
scikit-learn

Dockerfile:

FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["python", "process.py"]

Build and run:

docker build -t my-pipeline .
docker run my-pipeline

Run with a mounted volume (so the container reads/writes local files):

docker run -v $(pwd)/data:/app/data my-pipeline

Useful Commands Reference

Command What it does
docker ps List running containers
docker ps -a List all containers (including stopped)
docker images List local images
docker stop <id> Stop a running container
docker rm <id> Remove a stopped container
docker rmi <image> Remove an image
docker logs <id> View container logs
docker exec -it <id> bash Shell into a running container

That’s all you need to get Docker running on Ubuntu. The same steps work on a fresh EC2 instance — just SSH in first and run them from there.