Objective

In this lab, students will:

• Run Docker containers

• Compare imperative and declarative deployment methods

• Create a deployment template using Docker Compose

• Explore Docker volumes

• Demonstrate persistent storage

• Relate Docker concepts to cloud computing concepts

By the end of this lab, students will understand how modern cloud applications are deployed and how persistent storage works.

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Background

Docker allows applications to run inside lightweight containers.

Containers are commonly used in:

• AWS ECS

• AWS EKS

• Azure Container Apps

• Azure Kubernetes Service (AKS)

• Google Cloud Run

• Google Kubernetes Engine (GKE)

There are two common approaches to deploying containers:

Imperative Approach

The administrator issues commands directly.

Example:

docker run ...
docker stop ...
docker rm ...

This is similar to manually launching a cloud virtual machine.

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Declarative Approach

The administrator describes the desired deployment in a configuration file.

Example:

compose.yaml

Docker automatically creates the required resources.

This is similar to:

• AWS CloudFormation

• Azure ARM Templates

• Terraform

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Part 1 – Verify Docker Desktop

Open Docker Desktop.

Verify:

Engine running

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Part 2 – Verify Docker Installation

Open PowerShell.

Execute:

docker version

Verify both:

Client
Server

appear.

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Part 3 – Explore Docker Desktop

Observe the following sections:

• Containers

• Images

• Volumes

Discussion:

Docker Desktop provides a graphical interface for managing Docker resources.

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Part 4 – Imperative Deployment

Step 1 – Run Python Web Server

Execute:

docker run -d `
--name python-web `
-p 8000:8000 `
python:3.9-slim `
python3 -m http.server 8000

Explanation:

Option	Description
-d	Run in background
--name	Container name
-p	Port mapping
python:3.9-slim	Image
python3 -m http.server	Application

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Step 2 – Verify Container

Execute:

docker ps

Expected:

python-web

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Step 3 – Open Browser

Browse to:

http://localhost:8000

A directory listing page should appear.

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Step 4 – View Logs

Execute:

docker logs python-web

Observe web access activity.

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Step 5 – Stop Container

docker stop python-web

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Step 6 – Remove Container

docker rm python-web

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Discussion

This deployment was performed manually.

To recreate it later, the administrator must remember the entire command.

This is known as an imperative deployment.

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Part 5 – Declarative Deployment

Step 1 – Create Project Folder

mkdir docker-template-demo
cd docker-template-demo

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Step 2 – Create compose.yaml

Create:

compose.yaml

Insert:

services:

  python-web:
    image: python:3.9-slim
    container_name: python-web

    command: python3 -m http.server 8000

    ports:
      - "8000:8000"

Save the file.

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Step 3 – Deploy Template

Execute:

docker compose up -d

Docker reads the template and creates the container automatically.

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Step 4 – Verify Deployment

docker compose ps

Expected:

python-web

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Step 5 – Open Browser

Browse to:

http://localhost:8000

The web server should appear again.

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Step 6 – Remove Deployment

docker compose down

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Discussion

The deployment definition is stored inside:

compose.yaml

This is similar to:

• AWS CloudFormation Templates

• Azure ARM Templates

• Terraform Files

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Part 6 – Create Persistent Storage

Step 1 – Update compose.yaml

Replace the file contents with:

services:

  python-web:
    image: python:3.9-slim

    container_name: python-web

    command: python3 -m http.server 8000

    ports:
      - "8000:8000"

    volumes:
      - website-data:/data

volumes:

  website-data:

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Step 2 – Deploy Again

docker compose up -d

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Step 3 – Verify Volume Creation

docker volume ls

Expected:

website-data

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Part 7 – Explore Volume

Open container shell:

docker exec -it python-web sh

Verify volume contents:

ls /data

Observe:

(empty)

The volume is newly created.

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Step 2 – Store Data

echo "Cloud Plus Storage Lab" > /data/storage.txt

Verify:

cat /data/storage.txt

Expected:

Cloud Plus Storage Lab

Exit:

exit

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Part 8 – Demonstrate Persistence

Remove deployment:

docker compose down

Deploy again:

docker compose up -d

Open shell:

docker exec -it python-web sh

Verify:

cat /data/storage.txt

Expected:

Cloud Plus Storage Lab

The file still exists.

Exit:

exit

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Discussion

The container was recreated.

The volume remained.

This is persistent storage.

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Cloud Storage Comparison

Docker Concept	Cloud Equivalent
Container	EC2 Instance
Docker Image	AMI
Compose Template	CloudFormation Template
Volume	EBS Volume
docker run	Manual Deployment
docker compose up	Template Deployment

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Reflection Questions

1. What is the difference between imperative and declarative deployment?

2. What advantages does a deployment template provide?

3. Why is Compose similar to CloudFormation?

4. Why did the volume survive when the container was recreated?

5. How is a Docker volume similar to AWS EBS?

6. Why is persistent storage important for applications?

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Learning Outcomes

After completing this lab, students will be able to:

• Deploy containers imperatively

• Deploy containers declaratively

• Create deployment templates using Docker Compose

• Create and use Docker volumes

• Demonstrate persistent storage

• Relate Docker concepts to cloud infrastructure concepts

• Understand template-based deployment strategies used in cloud environments