Case Study

Connected Healthcare Network Organization scales up their release cycle with nil downtime

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Amazon EKS, Amazon VPC, Amazon EC2, Application Load Balancer, AWS IAM, AWS WAF,  Amazon OpenSearch, AWS Lambda, Amazon API Gateway, Amazon DynamoDB, AWS Code Pipeline, AWS Code build.


Achieve a robust and scalable containerization solution for an EKS cluster, and implement a CI/CD pipeline for automated and efficient software releases.

About the Client

MedPay is a tech company creating an API platform named MedPay® Connected Care Network (CCN) that connects healthcare service providers with insurers. MedPay provides Healthcare IT services to providers, patients, and payers, including provider payment software, invoicing, bill processing, provider applications, insurance payments, loyalty programs, and other tools and services.



Downtime lowered post-implementation


Increase in availability achieved

Successfully incorporated microservices

DevOps Best Practices Implementation

The Challenge

Modernize and containerize the application for better deployment, scaling and independent applications with around 20 customer-facing applications in each environment. The current infrastructure has scalability and security issues and cannot withstand supporting a huge customer base.


  • Provision and implemented Amazon VPC design by following security best practices and network requirements for stage and prod environments
  • Provisioned an Amazon EKS cluster for high availability and autoscaling microservices in multiple environments with load balancing using the right instance types.
  • Implemented a CI/CD architecture better to build management in both stage and prod environments.
  • Deployed continuous delivery process for applications using Argo CD and Argo CD Rollouts.
  • Implemented a monitoring and alerting system using Prometheus and Amazon CloudWatch to monitor CPU and memory utilization of nodes and infrastructure monitoring on Amazon EKS.
  • Implemented Amazon OpenSearch stack for centralized log aggregation with Amazon CloudWatch logs.
  • Implemented container security using the grype tool to scan and check Docker images for vulnerabilities before pushing them to Amazon ECR, with image tagging.
  • Deploying required configs using configMaps for Data encryption and secure storage.
  • Implementing auto scaling for pods and nodes based on custom metrics.
  • Implemented a secure Amazon EKS cluster with restricted access, private subnet, dedicated IAM roles and service accounts, secure authentication, and image vulnerability checks.

The Results

Successful DevOps implementation with containerization supports new feature releases with zero downtime and deployments spanning within minutes.

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