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Migration to the Cloud with Serverless Architecture

Introduction

A leading supply chain management (SCM) solutions provider relied on a legacy on-premise infrastructure to support its core business operations. As the company grew, the system struggled to handle peak traffic efficiently. Maintenance windows caused frequent downtime, and scaling required manual provisioning, increasing both operational costs and risk. 

To support business agility and optimize costs, the organization decided to migrate its SCM application to the AWS Cloud using a serverless architecture, ensuring scalability, high availability, and a significant reduction in infrastructure management overhead. 

Challenges

The legacy setup created multiple operational inefficiencies and financial drains:

 

  • High operational costs: Overprovisioned compute and storage resources led to wasted capacity and inflated infrastructure expenses. 
  • Limited scalability: Static servers could not auto-scale during spikes in supply chain transactions, causing performance slowdowns during peak hours. 
  • Manual deployments: Rollouts and rollbacks required manual intervention, often introducing errors and extended downtime. 
  • Downtime during maintenance: Updates to infrastructure or applications frequently caused service interruptions and delayed business operations. 
  • Lack of monitoring visibility: Limited real-time monitoring made it difficult to detect and resolve issues proactively. 

The company needed a resilient, cost-effective, and automated solution that could scale seamlessly and reduce the DevOps burden. 

Our Solution

We re-engineered the SCM application using a serverless, AWS-based architecture designed for performance, flexibility, and cost optimization. 

Key solution components included:

 

  • Serverless migration with AWS Lambda: Replaced stateful services with stateless Lambda functions, improving scalability and eliminating idle server costs. 
  • Event-driven architecture: Implemented API Gateway for seamless request handling and DynamoDB for low-latency data operations. 
  • Infrastructure as Code (IaC): Used Terraform for automated provisioning, configuration, and version-controlled deployments. 
  • Monitoring & optimization: Integrated CloudWatch and CloudFront for performance analytics, security monitoring, and global content delivery. 
  • Continuous integration & deployment (CI/CD): Automated build and release pipelines ensured faster, error-free deployments and simplified rollbacks. 

The new architecture provided elastic scalability, high fault tolerance, and a pay-per-use cost model, aligning perfectly with the company’s growth trajectory.

Results
  • 45% reduction in total infrastructure cost within the first year through the pay-per-use model. 
  • 99.99% uptime achieved with built-in redundancy and fault tolerance. 
  • 60% faster deployments through automated IaC and CI/CD integration. 
  • 35% reduction in DevOps workload, freeing teams to focus on innovation rather than maintenance. 
  • Zero downtime during updates or rollbacks, improving customer satisfaction and operational continuity. 
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