Case Study

A Supply Chain Firm Overcomes Infrastructure Challenges by Migrating to AWS

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Supply Chain


AWS CloudFormation, Amazon EKS, Amazon EC2, Amazon CloudWatch, Amazon ECR, AWS Elastic Load Balancing


99% faster app startup, 75% less tenant onboarding downtime, streamlined infrastructure provisioning, 10% cost savings via efficient scaling, and seamless zero-downtime CI/CD for feature releases.

About the Client

Blue Ridge Global, based in Atlanta, Georgia, specializes in advanced supply chain planning software. Their algorithms and machine learning optimize inventory, demand, and pricing strategies, serving a global customer base across industries with demand, inventory, price, and replenishment solutions. 


5-6 seconds

Improved Application Startup Time


Reduced Tenant Onboarding Downtime


Cost Savings

The Challenge

Blue Ridge Global faced scalability challenges due to a 50% growth in their customer base, necessitating a $500,000 infrastructure upgrade. Frequent maintenance and upgrade issues resulted in a monthly downtime of 10 hours. Inadequate monitoring hindered issue identification and resolution. To support their expanding customer base, they plan to transform their software into a SaaS offering, expecting a 20% revenue increase. 


  • Lift and shift migration of the legacy .NET application to Amazon EC2 instances. 
  • Installed IIS and other .NET dependencies on Amazon EC2 instances. 
  • Replaced on-premises VMs with Amazon EC2 instances. 
  • Migrated ASP.NET-based web applications and Windows scheduled tasks from Amazon EC2 to Amazon EKS with containerized architecture. 
  • Converted a multi-tenant web app into single-tenant instances with custom features for each tenant. 
  • Implemented Nginx ingress backed by Network Load Balancer for traffic management and AWS Autoscaling for high availability. 
  • Set up Amazon CloudWatch for custom metric analysis and real-time application logs for troubleshooting. 
  • Established continuous integration and continuous deployment using Bitbucket, Amazon ECR, TeamCity, and Octopus on Amazon EKS. 
  • Created and configured an Amazon EKS cluster on Linux and Windows nodes with cluster autoscaling. 
  • Implemented AWS Load Balancer Controller and Nginx Ingress Controller for external application access. 
  • Enabled Horizontal Pod Autoscaling (HPA) based on CPU and memory consumption. 
  • Set up infrastructure and application monitoring with Amazon CloudWatch and integrated Datadog with Amazon EKS. 
  • Leveraged AWS CloudFormation, Amazon EKS, Amazon EC2, Amazon CloudWatch, Amazon ECR, and AWS Elastic Load Balancing in the solution. 

The Results

Pods optimization, Rolling Updates, automation, efficient scaling, and seamless CI/CD enable drastic performance improvements and cost savings. 

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