A production-minded, full-stack serverless application designed to model how modern cloud systems are built, deployed, observed, and scaled.
While the user-facing domain is simple (task management), the underlying architecture intentionally mirrors real-world engineering constraints: stateless compute, least-privilege security, automated delivery, and operational visibility.
This project is primarily an infrastructure and DevOps learning system, not just a CRUD app.
- Create, edit, complete, and delete todos
- User-specific data isolation
- Responsive UI (mobile, tablet, desktop)
- Explicit loading, error, and empty states
- Dark / light mode support
- Optimistic UI updates for low-latency interactions
- Secure user authentication using JWTs
- Token validation enforced before business logic execution
- Users can only access their own data
- Authorization failures handled explicitly
This application follows a serverless, event-driven architecture.
- Next.js (React)
- Tailwind CSS
- Deployed as a static site via CDN
- API Gateway exposing REST endpoints
- AWS Lambda functions with single-responsibility handlers
- Stateless request handling
- No long-running servers
- Serverless database (DynamoDB or serverless Postgres)
- Data partitioned by user ID for horizontal scalability
- Indexed for fast read access
- Soft deletes and audit timestamps included
- Managed identity provider (e.g., Cognito)
- JWT-based authentication
- Authorization enforced at the API boundary
Security is treated as a layered system, not a checkbox.
- Least-privilege IAM roles for all services
- Secrets stored in a secrets manager (never committed)
- Strict CORS configuration
- Input validation on all endpoints
- Rate limiting at the API layer
- No implicit trust between services
All deployments are fully automated.
On every Git push, the pipeline:
- Runs linting and tests
- Builds frontend and backend artifacts
- Deploys infrastructure via Infrastructure as Code
- Supports fast rollbacks
- dev – active development
- staging – pre-production validation
- prod – stable, user-facing environment
Manual console changes are intentionally avoided.
All cloud resources are defined and versioned using IaC:
- API Gateway
- Lambda functions
- Database tables
- IAM roles and policies
- Logging and monitoring resources
The entire system can be destroyed and recreated from code alone.
Operational visibility is a first-class concern.
- Structured logs from all Lambda functions
- Centralized log aggregation
- Metrics for request count, latency, and error rates
- Alarms for failures and degraded performance
The system is designed to answer:
- What broke?
- When did it break?
- Why did it break?
Without relying on user reports.
The application is designed to scale automatically.
- Scales to zero during inactivity
- Handles traffic spikes without manual intervention
- Cost directly correlates to usage
Architectural considerations include:
- Cold start impact
- Database throughput limits
- API rate limits
- Expected bottlenecks at 1k, 100k, and 10M users
This project explicitly accounts for failure.
- Network latency and retries
- Lambda timeouts
- Permission misconfiguration
- Partial deployments
- Downstream service errors
Failures are observable, contained, and recoverable.
- Frontend: Next.js, React, Tailwind CSS
- Backend: AWS Lambda, API Gateway
- Database: DynamoDB / Serverless Postgres
- Auth: Cognito / Auth0
- IaC: Terraform / AWS CDK
- CI/CD: GitHub Actions
- Monitoring: CloudWatch (logs, metrics, alarms)
This project intentionally prioritizes:
- Simplicity over cleverness
- Explicit behavior over implicit assumptions
- Automation over manual processes
- Observability over optimism
The goal is not to build a perfect app, but a realistic system that behaves well under stress.
- Real-time updates using WebSockets or subscriptions
- Shared lists and collaborative editing
- Fine-grained role-based access control
- Advanced cost optimization strategies
MIT License
Most beginner projects optimize for speed.
This project optimizes for understanding.
It is a compact environment for learning how production systems are built, deployed, monitored, secured, and evolved over time.