AWS-Powered Data Migration and Serverless App Modernization for Emergency Response
Migrating a mission-critical emergency response platform from Google Cloud to AWS with faster data sync, elastic scaling, and stronger edge security
Lone Star Hazmat’s web and mobile applications on Google Cloud struggled with latency during high-traffic periods, limited scalability, and security exposure on public endpoints. KnackForge migrated the data layer to Amazon Aurora MySQL and modernized the application using AWS Lambda and AWS Fargate, improving field sync speed, deployment efficiency, and security using DataSync, CloudFront, and WAF.
Challenges
- Slow field data synchronization and delayed cross-platform updates impacted dispatch and reporting.
- Non-elastic compute caused underutilization during idle times and performance issues during spikes.
- Public endpoints lacked WAF protection and fine-grained access controls.
- Fragmented deployment workflows slowed releases and increased operational risk.
- Latency during high-traffic periods reduced responsiveness for field teams.
- Migration complexity required moving Google Cloud SQL workloads to Aurora MySQL with continuity.
The Solution
- Migrated structured data from Google Cloud SQL to Amazon Aurora MySQL using AWS DataSync with incremental sync support.
- Rebuilt event-driven backend workflows using AWS Lambda for ingestion, validation, and dispatch notifications.
- Deployed API and processing services on AWS Fargate (ECS) for scalable, containerized workloads.
- Centralized document uploads and field reports in Amazon S3, delivered through Amazon CloudFront for low-latency access.
- Protected web access using AWS WAF and routed traffic using Route 53 and ALB.
- Automated build and releases using AWS CodePipeline with secrets managed in AWS Secrets Manager.
The Impact
With KnackForge Cloud Services in place, the customer experienced:
- Deployment time reduced from ~45 minutes to ~12 minutes (73% improvement).
- API response latency improved from ~900ms to ~500ms (44% reduction).
- Data synchronization delay reduced from ~5 minutes to ~30 seconds (90% faster).
- Field data processing time dropped by 40% using Lambda-triggered workflows and queue-based decoupling.
- Field report upload failures reduced from ~8% to less than 1%.
- Security alerts dropped from 3 in the prior 6 months to 0 post-deployment after WAF and endpoint hardening.
Technologies Used:
- AWS Lambda
- Amazon ECS (AWS Fargate)
- Amazon Aurora MySQL
- AWS DataSync
- Amazon S3 and Amazon CloudFront
- AWS WAF (with Route 53, ALB, and supporting CI/CD services)