The Patient Management System is a backend platform designed to efficiently manage patient information in a healthcare setting.
This project aims to solve complex problems in the medical domain by offering a scalable, secure, and fast microservices-based architecture.
Key Features:
- Full CRUD (Create, Read, Update, Delete) operations for patient records.
- Secure and scalable microservices architecture.
- Real-time communication between services using Kafka and gRPC.
- Cloud-ready deployment using Docker and Infrastructure as Code (IaC).
- Java Spring Boot — Backend framework for building microservices.
- Spring Security — Secure authentication and authorization mechanisms.
- Hibernate — ORM tool for database operations.
- REST API — For exposing endpoints during the first phase.
- gRPC and Protobuf — High-performance communication between Patient and Billing services.
- Apache Kafka — Event-driven communication between services.
- Docker — Containerization of each microservice.
- AWS & LocalStack — Cloud deployment and emulation.
- Infrastructure as Code (IaC) — Automated infrastructure provisioning.
- Microservices Architecture — Six independent services communicating via Kafka messages and gRPC requests.
- Containerized Deployment — Each service is packaged as a Docker container for seamless deployment.
- Cloud Infrastructure — Built from scratch using IaC principles and deployed to AWS (tested with LocalStack emulator).
- Authentication & Authorization — JWT tokens and Spring Security implemented to protect all microservices.
- Scalability — Designed to easily scale horizontally by adding more instances of services.
- API Gateway — A single entry point for all client requests, managing routing, load balancing, authentication, and rate limiting.
- Local Development:
- Used LocalStack to emulate AWS services locally.
- Docker Compose orchestrates multiple microservices for local testing.
- Cloud Deployment:
- Docker images can be pushed to AWS ECR (Elastic Container Registry).
- Infrastructure is created automatically using IaC (AWS CDK).
- Docker
- Java 21+
- Maven
- AWS CLI
- Implementing a Frontend app using ReactJS and a mobile app using React Native.
- Adding an AI feature to be able to handle and predict medicamentation for each patient.
- Providing automated reports on each patient.