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Faster Transaction Processing
Annual Housing Revenue Protected
Students Served Across 25+ Residence Halls
University Enrollment
Legacy Infrastructure: Transitioned from aging, on-premises servers that hindered modern performance.
Performance Bottlenecks: Eliminated sluggish transaction processing during high-traffic events like room selection.
Data Fragmentation: Resolved the issue of disconnected silos across housing, billing, and student records.
Operational Invisibility: Provided administrators with a unified view of operations to replace fragmented data sets.
Manual Integration Hurdles: Streamlined outdated processes and integrations that created departmental bottlenecks.
Scalable AWS Architecture: Engineered a cloud-native environment that integrates seamlessly with PeopleSoft while removing legacy performance barriers.
Unified Data Integration: Built custom ETL pipelines using AWS DMS and AWS Glue to consolidate fragmented data systems.
30% Faster Processing: Accelerated transaction speeds by 30%, ensuring rapid response times for critical operations.
Elastic Performance Scaling: Enabled the platform to scale automatically during peak surges, preventing system degradation.
Revenue Protection: Built a high-reliability infrastructure to support and secure over $50M in annual housing revenue.
Our PeopleSoft System Can't Handle Peak Loads 
Housing and Student Data Live in Silos 
We're Running on Aging On-Prem Hardware 
Our IT Team Spends Too Much Time Firefighting 
We Can't Scale for a Growing Student Body 
Conducted a thorough Operational Level Agreement and workload assessment to identify bottlenecks, map dependencies, and establish performance baselines before any migration work began.
Built cloud-native solutions on AWS with design reviews ensuring alignment with industry standards. Built for elastic scalability to handle enrollment surges and peak housing events.
Built custom ETL pipelines using AWS DMS and AWS Glue to break down data silos between PeopleSoft, housing management, billing, and student information systems.
Implemented continuous performance monitoring and optimization to sustain the 30% transaction speed improvement, ensuring reliability during critical periods like room selection and move-in.
Elastic Compute Cloud (Scalable Virtual Servers)
Relational Database Service (Managed Databases)
Simple Storage Service (Scalable Object Storage)
Serverless Compute Service (Run Code on-demand)
Managed API Management Service
Content Delivery Network (CDN)
Scalable Domain Name System (DNS)
Migrate Databases to AWS
Serverless Data Integration Service (ETL)
OLA Assessment, workload analysis, and architecture design
AWS infrastructure buildout, ETL pipeline development
PeopleSoft integration, data migration, and testing
Optimization, monitoring, mentorship program, and handoff
Beyond the technical deliverables, CloudLogically embedded Computer Science and Corps of Cadets students into the project team as research assistants.
These students gained hands-on experience with enterprise-grade AWS architecture, ETL pipeline development, and real-world software engineering practices — accelerating their career readiness while contributing meaningful work to the project.
CloudLogically also mentored junior developers and onboarded new team members within the Department of IT, ensuring long-term knowledge transfer and self-sufficiency after the engagement concluded.
Students Embedded as Research Assistants
Real-World AWS & Software Engineering Training
Mentored & Onboarded Within IT Department
Knowledge Transfer for Long-Term Self-Sufficiency
We’ve received your request for an AI Readiness, Safety, and Security Assessment.
A member of our advisory team will review your submission and reach out within 1–2 business days to discuss next steps. This initial conversation is exploratory and focused on understanding your context, not selling services.
We’ve received your request for an AI Readiness, Safety, and Security Assessment.
A member of our advisory team will review your submission and reach out within 1–2 business days to discuss next steps. This initial conversation is exploratory and focused on understanding your context, not selling services.