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Letting Data Speak, AI Act!
Case Study
Azure to AWS SaaS Platform Migration
About the Client
A fast-growing EdTech SaaS company serving K–12 school districts in the US, operating a cloud-hosted student risk monitoring and intervention platform that helps school leaders identify and address student risks in mental health, behaviour, and academics. Facing rapid district adoption and imminent market expansion, the client needed a scalable, secure, and cost-optimised cloud foundation.
Challenge
The client's entire SaaS platform ran on Microsoft Azure — 17 VMs, 12 PostgreSQL Flexible Servers, 704 GB of disk storage, 8 storage accounts, and multiple App Services with integrations including KeyCloak, GrowthBook, SendGrid, SFTP, and ETL/Talend pipelines. To unlock AWS education equity credits and support onboarding of a new California school district, a full lift-and-shift migration was required — without disrupting live school district operations — all within a 9-week window timed to a low-usage academic period.
Key Results
Achieved 40% reduction in cloud infrastructure operating costs by migrating to AWS and leveraging AWS education equity credits, generating significant recurring annual savings.
Successfully migrated 17 virtual machines, 12 PostgreSQL databases, 704 GB of disk storage, and 8 storage accounts to AWS within a 9-week timeline with zero data loss.
Completed production cutover during a planned low-usage period between academic years, resulting in zero disruption to school district operations and continued support for at-risk student monitoring.
Established a fully automated CI/CD pipeline using AWS-native services, reducing deployment cycle time by 20%.
Enabled rapid onboarding of a new California school district post-migration by provisioning a scalable, multi-account AWS environment designed for growth.
Solution
Using an agile, iterative approach, the team executed a full Azure-to-AWS migration across three phases: foundation setup, core migration, and testing/cutover.
AWS Organization & Infrastructure: Provisioned AWS Control Tower with a multi-account Landing Zone (Dev, QA, Staging, UAT, Prod) and foundational infrastructure via Terraform — VPCs, subnets, IAM roles, security groups, and CloudWatch monitoring with SSO/MFA access patterns.
VM & Database Migration: Migrated 17 VMs to Amazon EC2 and 12 Azure PostgreSQL Flexible Servers to Amazon RDS for PostgreSQL, with full data integrity, automated backups, and security configurations.
Storage & Application Migration: Transferred 704 GB to Amazon EBS/S3 and re-platformed Azure App Services and Function Apps to Elastic Beanstalk, Lambda, and ECS. Deployed Node.js and React workloads, and migrated SendGrid, SFTP, and ETL/Talend pipelines to AWS-native services.
Auth, Feature Flagging & CI/CD: Re-configured KeyCloak and GrowthBook in the AWS environment. Implemented a full CI/CD pipeline using AWS CodeCommit, CodeBuild, CodeDeploy, and CodePipeline.
Testing & Cutover: Conducted end-to-end functional, performance, load, and UAT testing. Executed a zero-downtime production cutover aligned to the academic off-period, followed by documentation, knowledge transfer, and project closeout.
Technologies Used
Amazon Web Services (AWS): EC2, RDS for PostgreSQL, S3, EBS, ECS, AWS Control Tower, VPC, IAM, CloudWatch
Terraform – Infrastructure-as-Code for provisioning foundational AWS resources
AWS CI/CD Suite: CodeCommit, CodeBuild, CodeDeploy, CodePipeline
KeyCloak – Identity and access management / user authentication
GrowthBook – Feature flagging and experimentation platform
Azure PostgreSQL Flexible Server / Amazon RDS for PostgreSQL – Managed relational database services
ETL/Talend – Data processing pipeline tooling
SendGrid – Transactional email service integration
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