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Cloud Infrastructure Optimization and Cost Reduction for EdTech Platform
  1. case
  2. Cloud Infrastructure Optimization and Cost Reduction for EdTech Platform

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Cloud Infrastructure Optimization and Cost Reduction for EdTech Platform

trigent.com
Education
Information technology
Business services

Cloud Infrastructure Challenges

Rapid growth through acquisitions resulted in a fragmented AWS environment with 20+ services, Kubernetes sprawl, inefficient Twilio usage, and technical debt. Lack of architecture visibility and cost control led to 30% overspending on cloud infrastructure.

About the Client

Global EdTech leader providing student enrollment solutions through digital experiences, video production, and data analytics for higher education institutions

Key Project Goals

  • Reduce AWS infrastructure costs by 30% annually
  • Optimize Kubernetes (EKS) and database (RDS) efficiency
  • Implement serverless architecture for microservices
  • Improve Twilio messaging cost efficiency
  • Resolve technical debt in legacy components

Core System Requirements

  • AWS architecture visualization and analysis
  • Kubernetes cost tracking with Kubecost integration
  • Automated RDS instance optimization
  • Twilio message cost reduction engine
  • Serverless migration framework for microservices
  • Centralized cloud resource dashboard

Technology Stack

AWS EKS
Amazon RDS
AWS Lambda
Kubecost
Ruby on Rails
Python
CloudWatch Logs

System Integrations

  • Twilio Messaging API
  • AWS Well-Architected Tool
  • ElastiCache
  • Legacy Stencil.js/Ionic frontend

Operational Requirements

  • Auto-scaling infrastructure with 99.9% uptime
  • Real-time cost monitoring dashboard
  • Data encryption for compliance
  • Seamless migration path for legacy systems
  • Performance optimization for global access

Business Impact Projections

Projected 30% reduction in annual AWS costs ($250K+ savings), 45% fewer Kubernetes instances, optimized database performance, and improved system scalability to handle 50% more user traffic with minimal cost increases while maintaining existing technology stack stability.

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