Snaptec
Case Study

Baytonia E-Commerce Platform

  • The Challenge Four Engineering Problems That Demanded Custom Solutions Baytonia required an enterprise commerce platform that could scale dynamically, personalize experiences using machine learning, deploy continuously without downtime, and operate with zero data loss — all while staying anchored in AWS Bahrain. 01 ML in an unsupported region AWS Personalize was unavailable in Bahrain A cross-region replication model was needed to unlock recommendation intelligence without moving Baytonia’s core commerce infrastructure outside me-south-1. 02 Regional CI/CD limitation No native GitLab to CodePipeline integration Deployments were manual, slow, and risky, taking 30+ minutes each with no rollback automation and only 1–2 releases per week possible. 03 High availability at enterprise scale Traffic spikes demanded zero-loss resilience The platform needed to absorb 10,000–50,000 requests per day, survive 10x surge periods, and maintain sub-60-second failover with RPO = 0. 04 Real-time personalization Recommendations had to respond live User events such as views, add-to-cart actions, and purchases needed to power both real-time and batch recommendation experiences across the storefront. “Baytonia didn’t need a standard cloud deployment. It needed a region-aware enterprise architecture that could solve for scale, ML, resilience, and shipping velocity at the same time.” — SnapTec engineering perspective The Solution Three Integrated Systems, Engineered From Scratch SnapTec designed a tightly connected system spanning machine learning, fault-tolerant AWS infrastructure, and automated deployments — each layer purpose-built around Baytonia’s regional and operational constraints. ① 01 AWS Personalize ML integration We built a custom serverless ML pipeline to enable real-time and batch product recommendations, despite AWS Personalize not being available in Bahrain. 5 Lambda functions for export, analysis, import, campaigns, and orchestration
  • Aurora RDS cross-region replica from Bahrain to Ireland
  • Real-time JavaScript SDK for event tracking
  • Custom Magento GraphQL resolvers for homepage, PDP, and email feeds
  • Event-driven S3 pipeline for automated dataset imports and retraining

Multi-AZ high availability architecture

Baytonia’s core commerce stack was re-architected across two availability zones with automated failover, proactive monitoring, and zero data loss for critical components.

  • Frontend ASG (2–10 instances) and backend ASG (2–6 instances)
  • Aurora RDS Multi-AZ with automatic primary promotion
  • Redis Multi-AZ with sub-30-second failover
  • Application Load Balancer with health-based rerouting
  • 50+ CloudWatch alarms across compute, DB, cache, and queue layers

Automated CI/CD with Lambda webhook bridge

We created a custom webhook bridge connecting GitLab to AWS CodePipeline, solving the Bahrain-region integration gap and enabling safe rolling deployments with instant rollback.

  • Lambda transforms GitLab webhook payloads into CodePipeline-compatible triggers
  • CodeDeploy rolling releases with health-check validation
  • Automatic rollback in ~3 minutes when failure thresholds are hit
  • Deployment time reduced from 30+ minutes to 12 minutes
  • Solution cost ~ $46/month versus $500+/month third-party alternatives

Enterprise-grade technologies, precisely composed

Magento 2 on AWS, enriched with ML, automation, and region-aware infrastructure design.

Core Platform

Magento 2.x Enterprise, PHP 8.x, MySQL 8 Aurora RDS, Ubuntu 24 LTS, Nginx.

AWS Infrastructure

EC2 Auto Scaling, Aurora RDS Multi-AZ, ElastiCache Redis, Amazon MQ, OpenSearch, CloudFront, WAF, ALB.

ML & AI

AWS Personalize, Lambda functions, S3 ETL pipeline, real-time event tracking, custom recommendation delivery.

CI/CD Pipeline

AWS CodePipeline, CodeBuild, CodeDeploy, GitLab, and a custom Lambda webhook bridge for trigger orchestration.

Multi-AZ AWS Architecture at a Glance

The Baytonia platform was engineered as a layered system, from edge security and auto scaling through data resilience, ML personalization, and automated deployment infrastructure.

Measurable Outcomes From Day One

Baytonia gained infrastructure resilience, engineering speed, and machine-learning-powered personalization without compromising regional hosting requirements.

Uptime over 6 months

Post-migration reliability held steady across enterprise load, monitored with alarms across all critical layers.

Production deploys per day

Engineering velocity scaled dramatically from a former 1–2 releases per week model.

Deployment time

Fully automated release workflows replaced slow manual deployments and reduced operational risk.

Annual CI/CD savings

Custom automation avoided costly third-party tooling and improved economics at the same time.

3-minute automatic rollback

Health-check-triggered rollback protects production with a 5% failure-rate threshold and fast recovery on deployment issues.

Zero data loss (RPO = 0)

Synchronous Aurora replication across availability zones ensured no critical data loss under failure scenarios.

Real-time ML recommendations

Live recommendation blocks powered homepage, product pages, and email campaigns using AWS Personalize-driven inference.

10x traffic spike resilience

Auto scaling absorbed Black Friday-level spikes from 10K to 50K requests/day automatically without service disruption.

What Enterprise Commerce Teams Can Learn

The Baytonia project proves that regional limitations do not need to limit innovation. With the right engineering strategy, enterprise commerce teams can unlock ML, high availability, and deployment speed simultaneously.

Regional cloud constraints can be engineered around

Unsupported services do not have to block capability. Cross-region replication and serverless orchestration can unlock enterprise ML while keeping core infrastructure regionally aligned.

Deployment speed is a competitive advantage

Moving from weekly manual releases to daily automated deployments gives teams more room to test, improve, fix, and innovate without risking platform stability.

High availability must be designed, not assumed

True enterprise resilience comes from coordinated failover across compute, database, cache, routing, and monitoring layers — not just from moving workloads to the cloud.

Ready to Engineer Your Platform at This Scale?

SnapTec builds enterprise Magento platforms on AWS — from machine-learning-powered personalization to zero-downtime CI/CD and region-aware architecture design.