🌍 Project Overview
As part of a Architect Engineer assessment for XYZ Company, I was tasked with designing a secure, scalable, and reliable AWS-based architecture for a government-backed e-learning platform.
The goal was to create a system capable of serving up to 200 million users across multiple regions — supporting video streaming, quizzes, progress tracking, and a multilingual AI chatbot.
🧱 Architecture Goal
Design a 3-tier AWS architecture that ensures:
Scalability for millions of users
Security and compliance with government data standards
High availability across multiple Availability Zones
Cost efficiency using serverless and auto-scaling resources
⚙️ Core AWS Services Used
1️⃣ User Authentication & Access Management
Amazon Cognito for secure user authentication- Integrated with government identity providers via SAML/OAuth
Multi-Factor Authentication (MFA) enabled for all users- Role-based access for students, instructors, and administrators
2️⃣ Video Delivery and Streaming
Amazon S3 stores all course materials and videos
AWS Elemental MediaConvert handles video transcoding
Amazon CloudFront (CDN) delivers content with adaptive bitrate streaming for smooth playback across all regions- Content is secured using signed URLs and S3 encryption
3️⃣ Multilingual AI Chatbot
Amazon Lex powers the conversational interface
Amazon Translate automatically detects and translates languages- Chatbot supports English, Yoruba, Hausa, Igbo, and Pidgin
- Personalized responses based on user progress data stored in Aurora
4️⃣ Monitoring & Compliance
AWS CloudTrail logs all API activities for audit purposes
Amazon CloudWatch monitors performance metrics and triggers alarms
AWS Config ensures resource compliance with security policies
5️⃣ Quizzes & Progress Tracking
Real-time quiz scoring and feedback using AWS Lambda + API Gateway
- Data stored in Amazon Aurora (PostgreSQL) for structured consistency
DynamoDB used for low-latency user progress tracking
6️⃣ Data Storage & Analytics
| Data Type | AWS Service |
|---|---|
| Videos & Materials | Amazon S3 |
| User & Quiz Data | Amazon Aurora |
| Progress Tracking | Amazon DynamoDB |
| Analytics & Reporting | AWS Glue + Redshift (future phase) |
Here is the Native Design below:
🏗️ 3-Tier Architecture Design
Tier 1: Web Layer
- Deployed on Auto-Scaled EC2 instances behind an Application Load Balancer (ALB) in public subnets
Tier 2: Application Layer
- Stateless compute services (EC2 or AWS Lambda) in private subnets
Tier 3: Database Layer
Aurora Cluster in private subnets, Multi-AZ enabled with read replicas
Additional Infrastructure:
VPC with 6 subnets (3 public, 3 private across 3 AZs)
NAT Gateway for private subnet outbound access
Security Groups + Network ACLs for layered protection
CloudFront CDN for global performance acceleration
💰 Cost Optimization Highlights
Aurora Serverless v2 for automatic scaling of database capacity
S3 Intelligent-Tiering for optimizing storage costs
Spot Instances for EC2 auto-scaling groups
AWS Budgets + Cost Explorer for continuous cost monitoring
🧠 Key Outcomes
Highly available, fault-tolerant, and secure architecture- Optimized for millions of concurrent users
- Ready for NDPR/ISO compliance via CloudTrail and IAM governance
Inclusive learning through multilingual AI support
🧾 Deliverables
- AWS Architecture Diagram
- Statement of Work (SOW)
- Presentation Slide Deck
🚀 Conclusion
This project demonstrates the power of cloud-native architecture on AWS in enabling education at scale — bringing inclusive, accessible, and secure learning to millions of users across regions.
It also highlights my practical experience as a Cloud Engineer in building enterprise-grade solutions that combine scalability, security, and innovation.
📬 Connect With Me
👤 Bakre Jamiu (CloudWithHorla)
AWS Cloud & DevOps Engineer
✉️ [email protected]