Case study • Education Technology • Cloud Modernization Infrastructure
80% Infrastructure Cost Reduction by Migrating Online Learning Platform to AWS
We partnered with a leading U.S. online learning platform to modernize its infrastructure and resolve persistent performance and scalability issues. By migrating the application from Heroku to AWS and implementing a high-availability cloud architecture with optimized video streaming, we improved reliability, enabled massive transaction scalability, and reduced infrastructure costs by 80%.
Success Highlights
Key Details
Industry: Education Technology Geography: United States
Platform: Amazon Web Services (AWS)
Business Challenge
As online learning adoption accelerated, the client’s existing infrastructure struggled to support growing demand. The legacy stack deployed on Heroku introduced performance bottlenecks, high operational costs, and frequent availability issues.
Traffic spikes caused service disruptions due to limited scaling capabilities.
Our Solution Approach
We designed and executed a cloud-native migration strategy to modernize the platform, improve reliability, and optimize infrastructure costs.
1 · Discover
Assess Infrastructure Bottlenecks
Conducted a comprehensive assessment of the existing Heroku-based deployment to identify scalability limitations, cost inefficiencies, and performance bottlenecks.
2 · Consolidate
Design Resilient AWS Architecture
Architected a single-region, multi-Availability Zone deployment to ensure high availability, fault tolerance, and scalable infrastructure.
3 · Automate
Implement Cloud Infrastructure and CI/CD Pipelines
Built automated infrastructure provisioning and deployment pipelines to streamline application releases and ensure consistent environment management.
4 · Accelerate
Optimize Video Delivery and Application Performance
Implemented adaptive bitrate streaming, video transcoding pipelines, and edge caching to deliver high-quality video streaming at scale.
Technical Highlights
AWS multi-Availability Zone architecture ensuring fault tolerance and high availability Auto-scaling compute infrastructure for dynamic workload management during peak traffic
CI/CD pipelines enabling automated build, test, and deployment workflows Video streaming optimization using HLS adaptive bitrate streaming Edge caching via CDN distribution to reduce latency and improve video playback performance
// Python – Auto-Scaling Traffic Management
def scale_application(request_rate):
if request_rate > threshold_high:
increase_instances()
elif request_rate < threshold_low:
reduce_instances()
monitor_latency()
rebalance_load()
Business Outcomes
The cloud migration transformed the learning platform into a scalable, resilient system capable of handling high student demand while significantly reducing operational costs.
80%
Infrastructure Cost Reduction:
Optimized AWS resource allocation and auto-scaling policies dramatically lowered operational expenses.
7,000+
Transactions per Second:
The cloud-native architecture enabled the platform to handle heavy workloads and peak student activity without performance degradation
99.9%
Platform Availability:
Multi-AZ infrastructure improved uptime and ensured reliable access for schools and students nationwide.
Scalable infrastructure capable of supporting future platform growth
Looking to Modernize Your Learning Platform?
Let’s discuss how cloud-native architecture and performance optimization can help your platform scale reliably while reducing infrastructure costs.