Scaling Moodle LMS for 2,500+ Users on AWS

A High-Performance, Cost-Optimized Cloud Transformation

1. Executive Summary

This case study outlines the successful migration of a Moodle Learning Management System (LMS) from a traditional on-premise infrastructure to Amazon Web Services (AWS). The transformation has enabled the platform to seamlessly support over 2,500 concurrent users while achieving high availability (99.9% uptime), improved performance, and significant cost savings.

By leveraging AWS managed services and an intelligent auto-scaling architecture, the solution ensures scalability during peak academic loads while minimizing operational expenses during low usage periods.

2. Business Challenges (On-Premise Environment)

Key Limitations:

• High upfront capital expenditure for hardware and infrastructure
• Inability to handle sudden traffic spikes (e.g., exams, result publishing)
• Manual maintenance leading to downtime risks
• Limited disaster recovery capabilities
• Performance degradation during peak usage

Cost Factors:

• High initial infrastructure investment
• Ongoing maintenance and operational costs
• Scaling limitations leading to inefficient resource utilization

Impact:

• Poor user experience
• Limited scalability
• High operational overhead

3. Solution Overview (AWS Architecture)

A highly available and scalable architecture was designed using AWS services:

Compute Layer

• Amazon EC2 (Auto Scaling Group)
• Instance Type: c7i.xlarge
• Min: 2 | Desired: 2 | Max: 4

Database Layer

• Amazon RDS (MySQL/PostgreSQL)
• Instance: db.m5.large
• Multi-AZ deployment for high availability

Storage Layer

• Amazon EFS for shared application storage
• Amazon S3 for static assets and backups

Content Delivery

• Amazon CloudFront (CDN) for low-latency global delivery

Networking & Security

• Application Load Balancer (ALB)
• VPC with public and private subnets
• AWS WAF for web security

4. Auto Scaling Strategy

Scaling Policies:

• Scale Out: CPU > 70% OR increased request count
• Scale In: CPU < 30%
• Cooldown Period: 120 seconds

Outcomes:

• Automatic handling of traffic spikes
• Consistent performance during high-demand events
• Optimized infrastructure cost during off-peak hours

5. Performance Metrics

6. Cost Optimization

AWS Monthly Cost:

• More cost-efficient compared to traditional on-premises infrastructure.

Optimization Techniques:

• Auto Scaling reduces idle compute costs
• CloudFront minimizes backend load
• S3 lifecycle policies optimize storage costs

Cost Comparison:

• Savings: 30–40% reduction

7. Security & Reliability

• Network isolation using private subnets
• AWS WAF for application-layer protection
• Encryption at rest and in transit
• Automated backups via RDS and S3
• Multi-AZ deployment for failover resilience

8. Key Business Benefits

• Elastic scalability to handle dynamic workloads
• Pay-as-you-go pricing model
• High availability and fault tolerance
• Reduced operational burden
• Faster deployment and innovation cycles

9. Key Learnings

• Auto Scaling is critical for unpredictable workloads like LMS platforms
• Cloud-native architecture improves resilience and efficiency
• Proper cost optimization strategies significantly reduce expenses

10. Conclusion

Migrating Moodle LMS to AWS enabled a scalable, secure, and cost-efficient platform capable of supporting modern educational demands.

Architecture ensures high performance during peak loads while maintaining cost efficiency during low usage, making it an ideal solution for institutions transitioning to digital learning environments.