Retail / E-commerce12 months

E-commerce Platform: Legacy Spring to Spring Boot Cloud-Native

National Retail Chain

$320K/year
Infrastructure Savings
20x faster
Deployment Speed
15x faster
MTTR
300K users
Peak Traffic Handled
40% faster
Response Time
Daily
Deploy Frequency
The Challenge

The Challenge

A national retail chain operated an e-commerce platform built on legacy Spring Framework 3.2 with XML configuration. The monolithic application was deployed to on-premise servers, making scaling during peak seasons (Black Friday, holidays) extremely expensive and slow. The platform handled $500M in annual online revenue but couldn't scale quickly enough during traffic spikes. Infrastructure costs were high, deployment velocity was slow (monthly releases), and the development team struggled with the aging codebase. Critical requirements: - Must handle 100x traffic spikes during sales events - Need to reduce infrastructure costs - Cannot risk revenue loss during migration - Must enable continuous deployment - Need to modernize without rewriting business logic
Our Approach

The Solution

Executed a cloud-native modernization strategy: **Phase 1: Containerization & Cloud Prep (Months 1-2)** - Containerized existing application with Docker - Deployed to Kubernetes staging environment - Implemented health checks and monitoring - Set up CI/CD pipeline **Phase 2: Spring Boot Migration (Months 3-5)** - Migrated to Spring Boot 3 with minimal code changes - Converted XML configuration to Java config - Implemented Spring Boot Actuator for monitoring - Migrated to embedded Tomcat - Deployed to production with feature flags **Phase 3: Microservices Decomposition (Months 6-9)** - Extracted cart service as first microservice - Migrated product catalog to separate service - Implemented API Gateway pattern - Set up distributed tracing with OpenTelemetry - Migrated order processing service **Phase 4: Cloud-Native Optimization (Months 10-12)** - Implemented auto-scaling based on metrics - Added Redis for session management - Integrated with AWS managed services - Set up blue-green deployments - Implemented comprehensive monitoring dashboard
Outcomes

Results & Impact

Successfully handled Black Friday traffic (300K concurrent users) with zero downtime

Reduced infrastructure costs by 55% using auto-scaling

Deployment frequency increased from monthly to daily

Deployment time reduced from 4 hours to 12 minutes

Mean time to recovery (MTTR) reduced from 2 hours to 8 minutes

Page response time improved by 40%

Development team velocity increased 3.5x

Successfully processed $550M revenue in first year post-migration

"We went from dreading Black Friday to confidently scaling to any demand. The migration to Spring Boot and Kubernetes transformed our ability to compete in e-commerce."
Director of Engineering
National Retail Chain
Technology Stack

Before Migration

Spring 3.2
XML Config
Tomcat 7
On-Premise Servers
MySQL 5.6
Manual Deployments

After Migration

Spring Boot 3
Spring Cloud
Kubernetes
AWS EKS
Aurora PostgreSQL
Redis
API Gateway
GitLab CI/CD

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