A Simple AWS-Powered Clinic Appointment System App Using Docker and SNS

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Deploying full-stack applications on AWS doesn’t have to be overwhelming.

In this article, I’ll show how I built a basic Clinic Appointment Management System using Docker, FastAPI, and a few core AWS services. The app lets patients book appointments online, sends real-time notifications, and provides a secure way for admins to manage data - all in a lightweight and scalable setup.

If you're looking to get hands-on experience with deploying microservices on AWS, this beginner-friendly project is a great place to start!

Project Overview


This system enables:

• Patients to book appointments via a simple web UI.
• Real-time SMS/email notifications using AWS SNS.
• Admins to access the backend securely through OpenVPN.

With its lightweight and modular setup, this architecture is well-suited for beginners and rapid prototyping.

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AWS Architecture Overview

1. VPC Setup

• CIDR Block: 12.0.0.0/16
• Split into Public and Private subnets for better isolation and control.
• Internet Gateway for public services.
• NAT Gateway to allow private instances to access the internet securely (for updates, etc.).

2. Public Subnet Components

Application Load Balancer (ALB)

• Routes incoming traffic (HTTP/HTTPS) to backend services.
• Secured via security groups that limit access to only web ports.

OpenVPN Server

• Deployed on an EC2 instance with an Elastic IP.
• Allows secure, encrypted access to internal services.
• Only accessible on UDP Port 1194.

3. Private Subnet Components


This is where the core application logic lives - isolated from the internet.

Dockerized Microservices


Deployed on an EC2 instance using Docker Compose, the system includes:

Service	Port	Description
Frontend	8000	Public-facing web UI
Patient Service	8001	Manages patient registration/data
Doctor Service	8002	Manages doctors and schedules
Appointment Service	8003	Handles bookings and availability
Notification Service	8004	Sends confirmations via SNS

Each service uses a lightweight python3.12-slim base with FastAPI + Uvicorn for rapid performance.

PostgreSQL Database

• Dockerized inside the private subnet.
• Stores patient, doctor, and appointment records.
• Only accessible from within the VPC.

4. Admin Access with OpenVPN

• Admins connect via a VPN client to access the private network.
• Once authenticated, the admin accesses the PostgreSQL instance within the private subnet using a SQL client.
• No direct database exposure to the internet - ever.

5. DNS & Multi-AZ Load Balancing

• The Application Load Balancer provides a DNS endpoint for the frontend.
• Services are deployed across multiple Availability Zones (us-east-1a & us-east-1b) to increase resilience.

6. Real-Time Notifications with AWS SNS

• 
  The Notification Service integrates with AWS SNS to send:
  
  • SMS messages
  • Email confirmations
• 
  SNS scales automatically and ensures reliable message delivery.
  

7. Security Practices


Security is built-in, not bolted on:

• IAM Roles & Policies: Restrict and manage AWS access.
• Security Groups: Only necessary ports are open.
• Private Subnets: Critical services are not internet-facing.
• OpenVPN: Admins can only access internal systems after authentication.

8. Monitoring & Observability

• 
  AWS CloudWatch tracks:
  
  • EC2 metrics
  • SNS delivery logs
  • Application logs from microservices

This helps in performance tuning and alerting.

9. Designed for Scalability

• Load Balancer enables horizontal scaling of services.
• Docker Microservices can be updated independently.
• SNS automatically handles messaging load increases.

10. Future Enhancements


Here’s what’s next on the roadmap to make this production-ready:

• Add HTTPS support using SSL on the Load Balancer.
• Use AWS RDS for managed PostgreSQL.
• Build a CI/CD pipeline (AWS CodePipeline).
• Migrate to ECS or EKS for better container orchestration.
• Use Route 53 for domain-level routing.
• Enable WAF, GuardDuty, Inspector for advanced security.
• Set up alerting for downtime or intrusions.

? Final Thoughts


This project taught me how to combine infrastructure best practices with microservices architecture, all while staying secure and scalable. It’s a solid base for health tech applications, appointment systems, and even e-commerce platforms.

If you're starting your journey with AWS, Docker, or cloud security, this architecture offers a hands-on example with real-world value.

Let me know what you think - and I’d love to hear how you would extend or improve this setup!

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