Docker Deployment in AWS EC2

Nagaraj M
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Article

Pre-requisites to understand this

Basic understanding of Linux (processes, ports, SSH)
Familiarity with AWS EC2
Basic knowledge of Docker
- Images
- Containers
- Dockerfile
- IP, ports
- HTTP/HTTPS
- CI/CD basics
- Git and source code repositories

Introduction

AWS EC2 (Amazon Elastic Compute Cloud) is a core service provided by Amazon Web Services that allows you to rent virtual servers (called instances) in the cloud. These servers can be used to run applications, websites, databases, APIs, or any compute workload without needing to buy or maintain physical hardware. EC2 provides flexible, scalable, and on-demand computing capacity.

Docker deployment on EC2 is a common and powerful approach to running applications in the cloud. In this model, Amazon EC2 provides virtual machines, and Docker provides application containerization. The application is packaged along with its dependencies into Docker images, ensuring consistent behavior across environments. EC2 gives full control over infrastructure, while Docker simplifies application lifecycle management such as build, ship, and run.

What problem we can solve with this?

Traditional deployments often suffer from inconsistencies between environments (development, testing, production). Docker deployment on EC2 solves these issues by standardizing application runtime environments and simplifying scalability and maintenance.

Problems solved:

Environment mismatch (“works on my machine” issue)
Manual dependency installation
Complex deployment steps
Application conflicts on the same server
Difficult rollbacks
Poor scalability without orchestration

How to implement/use this?

Docker deployment on EC2 involves provisioning an EC2 instance, installing Docker, building or pulling Docker images, and running containers.

High-level steps:

Create an EC2 instance
Install Docker on EC2
Pull from Docker Hub / ECR
Run Docker container
Expose application using EC2 Security Groups
(Optional) Add Load Balancer / Auto Scaling

Docker Deployment Flow (Sequence Diagram)

This sequence diagram explains how an application is deployed using Docker on EC2.

Step-by-step explanation:

Developer pushes code to a Git repository
Developer connects to EC2 using SSH
Docker engine on EC2:
Builds an image from Dockerfile
Creates a container from the image
Container starts the application
Application is accessed using EC2 Public IP and exposed port

Docker Deployment Architecture (Component Diagram)

This component diagram represents the structural architecture of Docker deployment on EC2.

Components explained:

Component	What it is	Role in Docker Deployment on EC2	Example
User Browser	Client application (browser or API client)	Sends HTTP/HTTPS requests to access the application	Chrome browser calling http://ec2-ip:8080
EC2 Instance	Virtual server in AWS cloud	Hosts Docker Engine and provides compute, storage, and networking	t2.micro EC2 instance
Docker Engine	Container runtime installed on EC2	Builds images, creates containers, starts/stops containers	dockered service
Docker Image	Read-only template with app & dependencies	Acts as a blueprint to create containers	nginx:latest, my-app:v1
Docker Container	Running instance of a Docker image	Executes the application in an isolated environment	Running Nginx container
Application	Business logic or service	Handles user requests and returns responses	REST API, Web UI

Key architectural insights:

Application is isolated inside a container
Docker engine controls lifecycle
EC2 provides compute and networking

Advantages

Environment consistency
Faster deployments
Easy rollback using image versions
Isolation between applications
Better resource utilization
Works well with CI/CD pipelines
Full control over infrastructure
Cost-effective for small to medium workloads

Summary

Docker deployment on EC2 combines the flexibility of virtual machines with the portability of containers. It allows teams to package applications once and deploy them reliably across environments. While it requires some infrastructure management, it provides full control and is ideal for teams not ready for full container orchestration platforms like Kubernetes. This approach is widely used for production systems, microservices, and legacy application modernization.