Beyond “It Works on My Machine”: Getting Started with Docker

Deploying your first application on AWS is a useful milestone. But what happens when you need to deploy it again—or help a teammate run the same application?

You might discover a different runtime version, a missing dependency, or a setup step you forgot to document.

Docker helps make an application's environment more consistent. That makes it a practical next step after learning cloud deployment.

What does Docker actually do?

Docker lets you package an application and its dependencies into an image, then run that image as a container.

Three terms are worth understanding:

• Dockerfile: Instructions for building an image.
• Image: The packaged files and configuration used to create containers.
• Container: A running instance of an image.

For example, a Python application can use an image containing its code, Python runtime, and required packages.

The host still needs a compatible container runtime, and settings such as credentials and network access still need configuration.

Run your first container

With Docker installed and running, open your terminal and enter:

docker run -d --name cloud-demo -p 127.0.0.1:8080:80 docker/welcome-to-docker

Open http://localhost:8080 in your browser.

Here’s what the command does:

• -d runs the container in the background.
• --name cloud-demo gives it an easy-to-reference name.
• -p 127.0.0.1:8080:80 connects port 8080 on your local machine to port 80 inside the container, accessible through localhost.
• docker/welcome-to-docker identifies the image to run.

Check the running container:

docker ps

Read its logs:

docker logs cloud-demo

When finished, stop and remove it:

docker stop cloud-demo
docker rm cloud-demo

You have now practised the basic container lifecycle: start, inspect, and clean up.

How does this connect to AWS?

In a direct EC2 deployment, you might install the runtime and dependencies on the server yourself.

With a container workflow, you build an image, store it in a registry, and run that image in your cloud environment.

This gives you a versioned application package you can test before deployment.

Docker still leaves important work to you: configuring permissions, managing secrets, storing persistent data, and monitoring the application.

Your next project: containerize an app you already know

Choose a small application you can already run locally.

1. Write a Dockerfile for it.
2. Build an image and run a container.
3. Confirm that its main endpoint works.
4. Check the logs when a request fails.
5. Document the configuration someone else needs to run it.

Use Docker’s Dockerfile guide as a starting reference.

Keep passwords and AWS credentials out of your image and repository. For applications that store data, plan how that data will survive container replacement.

Learn AWS and Docker with Coder Roots

At Coder Roots, our Cloud Computing with DevOps training connects AWS fundamentals with Linux, Docker, Kubernetes, Terraform, Git, and CI/CD.

If you want guided practice connecting these tools, explore the curriculum and training options:

👉 Explore Coder Roots Cloud Computing Training

👉 Visit the Coder Roots website

Which application would you containerize first—a portfolio website, a backend API, or a college project? Tell us in the comments.