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README.md

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+# Repository Overview
 
-# backend-microservices
+This repository showcases a robust microservices architecture comprising three distinct services: **Department**, **User**, and **Point**. The project emphasizes code reusability through a common container that initializes essential components such as logging, database connections, and environment variables.
 
-This repository showcases a microservices architecture with three distinct services: Department, User, and Point. <br/>
-The project emphasizes code reusability through a common container for initializing essential components like logging, database connections, and environment variables. 
-- Department service exposes a REST API endpoint /api/departments/v1/departments for retrieving department data, 
-- User service provides a similar endpoint /api/user/v1/users for user information.
-- Point service leverages gRPC to offer user point data, which is then consumed by the User service, demonstrating inter-service communication.
+## Services
+- Department Service:
+  Exposes a REST API endpoint: `/api/departments/v1/departments` for retrieving department data.
+- User Service:
+  Provides a REST API endpoint: `/api/users/v1/users` for accessing user information.
+- Point Service:
+  Utilizes gRPC to deliver user point data, which is consumed by the User service, effectively demonstrating inter-service communication.
 
+This design promotes modularity and scalability across the services.
 
+## Key Features
 
-This design promotes modularity and scalability across the services.
+### CI/CD Integration:
+The repository includes CI/CD workflows located in `.github/workflows`, which automate the deployment process to AWS Elastic Container Registry (ECR) and Elastic Container Service (ECS) servers. This ensures seamless updates and efficient management of service deployments.
+
+### Performance Monitoring
+- **Prometheus Metrics**: Integrated Prometheus metrics allow users to monitor the performance of each service in real-time. This feature provides insights into system health and resource utilization.
+
+- **Memory Profiling with pprof**: 
+  The project includes pprof for memory monitoring, enabling developers to analyze memory usage and optimize performance effectively.
+
+### Testing Framework
+- **Integration Testing**: 
+  The system performs integration testing using a mock database running in a test Docker container. This setup ensures that all services interact correctly and maintain data integrity during operations.
+
+- **Unit Testing**: 
+  Comprehensive unit tests cover all code components, ensuring high code quality and reliability. Each service is rigorously tested to validate functionality and catch potential issues early in the development cycle.
+
+### Design Patterns and Architectural Choices
+- **Singleton Pattern**: Utilized in `lib/container/container.go` to ensure that only one instance of the container is created, managing logging, database connections, and environment variables efficiently.
+
+## Conclusion
+This microservices architecture not only demonstrates best practices in software design but also incorporates essential features for modern application development, such as CI/CD, performance monitoring, and robust testing frameworks. By leveraging these technologies, developers can build scalable, maintainable, and high-performing applications.