Technical Design Documents - Part 1 - Case-Study 1

Ulysses Alexandre Alves — Fri, 28 Nov 2025 16:48:42 +0000

On this video I talk about Technical Design Documents, a kind of artifacts which are key to the success of any software development project.

To give context to the lesson I use the technical design document that I created for my Cloud-Based Multi-Service Platform for Smart Event Management case-study project.

Software Requirements Specification - Case Study 1

Ulysses Alexandre Alves — Thu, 20 Nov 2025 20:32:49 +0000

Project Name: Cloud-Based Multi-Service Platform for Smart Event Management

Lecture about this content: https://www.youtube.com/watch?v=C4tE1kZNrX4

1. Introduction

The system is a cloud-native platform for managing large-scale events (conferences, concerts, workshops) with real-time analytics, ticketing, and personalized recommendations. It will integrate multiple services, each implemented in different languages, and leverage AI tools for development and intelligent features.

2. Overall Description

Purpose: Provide event organizers and attendees with a seamless experience for scheduling, ticketing, and engagement.
Scope:
- Web application for users (React + Node.js)
- Backend microservices (C#, Python, Go)
- AI-powered recommendation engine
- CI/CD pipelines for automated deployment
- Hosted on a major cloud (AWS, Azure, or GCP)

3. Functional Requirements

3.1 User Management Service (C# / .NET)

Register, authenticate, and manage user profiles.
Role-based access control (organizer, attendee).

3.2 Event Management Service (Go)

Create, update, and delete events.
Handle scheduling and capacity management.

3.3 Ticketing Service (TypeScript / Node.js)

Purchase and validate tickets.
Integrate payment gateway.

3.4 Recommendation Engine (Python)

Suggest events based on user preferences and past behavior.
Use AI/ML models for personalization.

3.5 Frontend (React)

Responsive UI for browsing events, purchasing tickets, and viewing recommendations.

4. Non-Functional Requirements

Performance:
- API response time < 200ms under normal load.
- Support 10,000 concurrent users.
Reliability:
- 99.9% uptime SLA.
- Automatic failover and load balancing.
Maintainability:
- Modular microservices architecture.
- Automated testing and linting integrated into CI/CD.

5. Technical Requirements

Cloud: AWS (EC2, S3, RDS, Lambda) or Azure/GCP equivalents.
CI/CD:
- Pipelines for each microservice using GitHub Actions or Azure DevOps.
- Automated build, test, and deployment.
AI Tools:
- Use Copilot or similar for code generation and refactoring.
- Integrate AI-assisted testing and documentation.
Automation:
- Infrastructure as Code (Terraform or AWS CDK).
- Automated dependency updates and security scans.
Languages:
- C# (.NET) for User Management
- Go for Event Management
- TypeScript (Node.js) for Ticketing
- Python for Recommendation Engine
Frontend: React (TypeScript).
Runtime: Node.js for frontend and ticketing service.

6. Architecture Overview

Microservices deployed in containers (Docker + Kubernetes).
API Gateway for routing requests.
Database:
- Relational DB for user and event data (PostgreSQL).
- NoSQL for recommendation engine (MongoDB).
Message Queue: RabbitMQ or Kafka for inter-service communication.

7. Security

OAuth 2.0 for authentication.
HTTPS for all endpoints.
Data encryption at rest and in transit.

8. Testing

Unit and integration tests for each service.
Load testing for performance validation.
Automated test execution in CI/CD pipeline.

Contact

If you would like to contact me to talk about this case study project or another subject, you can reach out to me through the comment sections, contact page or sending me a private message in my LinkedIn provile at https://www.linkedin.com/in/ulysses-alves/.

Thank you.

Forem: Ulysses Alexandre Alves