An enterprise-grade Employee Attendance Management System featuring biometric face recognition, role-based access control, leave management, real-time notifications, workforce analytics, geofencing, and secure authentication workflows.
This platform provides a complete workforce attendance solution built using a modern microservice architecture.
The system combines:
- Traditional authentication
- Face recognition login
- Attendance tracking
- Leave management
- Reporting & analytics
- Security monitoring
- Geofencing
- Real-time notifications
The project is designed for enterprise environments requiring scalability, security, reliability, and auditability.
- Traditional Username & Password Authentication
- Face Recognition Login
- Multi-Factor Authentication (MFA)
- JWT-Based Authentication
- Role-Based Access Control (RBAC)
- Security Monitoring & Audit Logging
- Employee Check-In / Check-Out
- Attendance History Tracking
- Real-Time Attendance Monitoring
- Attendance Analytics
- Geo-Fence Compliance Verification
- Face Enrollment
- Face Verification
- Face Login Authentication
- Anti-Spoofing Protection
- Liveness Detection
- Biometric Recovery Support
- Employee Management
- Leave Request Submission
- Leave Approval Workflow
- Department Monitoring
- Supervisor Dashboard
- Attendance Reports
- Employee Activity Reports
- Dashboard Analytics
- Exportable Reports
- Workforce Insights
- Docker Deployment
- Kubernetes Support
- Helm Charts
- Terraform Infrastructure
- Redis Caching
- WebSocket Notifications
- Health Monitoring
- Observability & Telemetry
graph TD
A[React + TypeScript Frontend] --> B[Node.js Express Backend API]
B --> C[(PostgreSQL Database)]
B --> D[(Redis Cache)]
B --> E[Face AI Service]
E --> F[(Face Database)]
B --> G[Authentication & Authorization]
B --> H[Attendance Management]
B --> I[Leave Management]
B --> J[Reporting & Analytics]
B --> K[Notification System]
B --> L[Geofencing Services]
G --> M[JWT Authentication]
G --> N[Role-Based Access Control]
H --> O[Employee Check-In]
H --> P[Employee Check-Out]
H --> Q[Attendance Analytics]
I --> R[Leave Requests]
I --> S[Leave Approval Workflow]
J --> T[Attendance Reports]
J --> U[Employee Analytics]
J --> V[Export Services]
K --> W[WebSocket Notifications]
K --> X[Real-Time Alerts]
L --> Y[Location Validation]
L --> Z[Geo-Fence Compliance]
AA[Nginx Reverse Proxy] --> A
AA --> B
AB[Docker Compose] --> AA
AB --> B
AB --> E
AB --> C
AB --> D
AC[Kubernetes] --> AB
AD[Helm Charts] --> AC
AE[Terraform Infrastructure] --> AC
| Component | Purpose |
|---|---|
| Frontend | Employee and Administrator interface |
| Backend API | Core business logic and API services |
| PostgreSQL | Core application data storage |
| Redis | Caching, session management, and performance optimization |
| Face AI Service | Face recognition, biometric authentication, and liveness verification |
| Face Database | Facial embeddings and biometric records |
| Authentication Service | JWT authentication and access control |
| Attendance Management | Check-in, check-out, and attendance tracking |
| Leave Management | Leave requests and approval workflows |
| Reporting & Analytics | Reports, analytics, and workforce insights |
| Notification System | Real-time alerts and WebSocket notifications |
| Geofencing Service | Location validation and compliance verification |
| Nginx | Reverse proxy and traffic routing |
| Docker Compose | Local container orchestration |
| Kubernetes | Production container orchestration |
| Helm | Kubernetes package management |
| Terraform | Infrastructure provisioning and automation |
- Users access the application through the React frontend.
- Requests are routed through Nginx to the Backend API.
- The Backend API handles authentication, attendance, leave management, analytics, and reporting.
- Face authentication requests are forwarded to the Face AI Service.
- User and attendance data are stored in PostgreSQL.
- Redis provides caching, session management, and performance optimization.
- Real-time updates are delivered through WebSocket notifications.
- Geofencing services validate employee locations during attendance operations.
- Docker and Kubernetes provide deployment and scalability infrastructure.
- JWT Authentication
- Face Recognition Login
- Multi-Factor Authentication (MFA)
- Password-Based Login
- Role-Based Access Control (RBAC)
- Employee Check-In
- Employee Check-Out
- Attendance History
- Attendance Analytics
- Real-Time Attendance Updates
- Face Enrollment
- Face Verification
- Face Login
- Anti-Spoofing Support
- Liveness Detection
- Face Embedding Management
- Leave Requests
- Leave Approval Workflow
- Work Reports
- Employee Tracking
- Supervisor Dashboard
- Attendance Reports
- Employee Statistics
- Dashboard Analytics
- Export Functionality
- Excel Report Generation
- Rate Limiting
- Security Monitoring
- Audit Logging
- JWT Security
- Helmet Security Headers
- Request Validation
- Telemetry Collection
- Distributed Tracing
- Health Monitoring
- Circuit Breakers
- Degraded Mode Support
- WebSocket Notifications
- React
- TypeScript
- Vite
- React Router
- Zustand
- Recharts
- Framer Motion
- React Webcam
- Node.js
- Express.js
- PostgreSQL
- Redis
- Socket.IO
- JWT
- Bcrypt
- Python
- Face Recognition Models
- OpenCV
- Anti-Spoofing Detection
- Liveness Verification
- Docker
- Docker Compose
- Nginx
- Kubernetes
- Helm
- Terraform
.
├── frontend/
│ ├── src/
│ ├── public/
│ └── package.json
│
├── backend-api/
│ ├── src/
│ ├── migrations/
│ └── package.json
│
├── face-ai-service/
│ ├── models/
│ ├── services/
│ └── requirements.txt
│
├── database/
│ └── init.sql
│
├── nginx/
│
├── deployment/
│
├── k8s/
│
├── helm/
│
├── terraform/
│
└── docker-compose.yml
- Manage users
- System configuration
- Security monitoring
- Face enrollment approval
- Access reports
- Platform administration
- Team oversight
- Attendance monitoring
- Leave approvals
- Workforce reporting
- Attendance check-in/out
- Face login
- Leave requests
- Personal reports
- Profile management
/login
/face-login
/setup/admin-face
/recovery-request
/dashboard
/attendance
/leave
/reports
/supervisor
/admin
/security
/system-status
git clone https://github.com/Arthur-2407/Employee-Management-System.git
cd Websitecp .env.example .envConfigure:
DB_NAME=attendance_system
DB_USER=postgres
DB_PASSWORD=<your_database_password>
FACE_DB_NAME=attendance_face_system
FACE_DB_USER=face_admin
FACE_DB_PASSWORD=<your_face_database_password>
REDIS_PASSWORD=<your_redis_password>
JWT_ACCESS_SECRET=<your_jwt_access_secret>
JWT_REFRESH_SECRET=<your_jwt_refresh_secret>Start all services:
docker compose up -d --buildCheck status:
docker compose psView logs:
docker compose logs -fStop services:
docker compose down| Service | Port |
|---|---|
| Frontend | 3000 |
| Backend API | 3001 |
| Face AI Service | 8000 |
| PostgreSQL | 5432 |
| Face PostgreSQL | 5433 |
| Redis | 6379 |
Backend:
curl http://localhost:3001/healthFace AI:
curl http://localhost:8000/health- JWT Access Tokens
- Refresh Tokens
- MFA Support
- Rate Limiting
- Request Validation
- Secure Headers
- Audit Logging
- Security Monitoring
- Face Verification Controls
- Application Telemetry
- Request Tracing
- Correlation IDs
- Health Monitoring
- Circuit Breakers
- Alerting Infrastructure
- Service Status Dashboard
Frontend:
cd frontend
npm install
npm run devBackend:
cd backend-api
npm install
npm run devFace AI Service:
cd face-ai-service
pip install -r requirements.txt
python app.pyThis project is licensed under the Apache License, Version 2.0.
You may obtain a copy of the License at:
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the LICENSE file for the specific language governing permissions and limitations under the License.