Case Study

HealthTech Startup Migrates Microservices to Amazon EKS for Enhanced Availability and Agility

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Amazon VPC, Amazon EC2, Amazon RDS, AWS Code Pipeline, AWS CodeBuild, Amazon API Gateway, Amazon DynamoDB, Amazon Route53, Amazon EKS


Empower customer’s business growth with a multi-environment setup in the AWS cloud, fortified by robust SLAs and a scalable, secure, and mobile-friendly application designed to handle high customer traffic.

About the Client

MedPay is a HealthTech with MedPay® Connected Care Network, an API platform linking healthcare providers and insurers for real-time payments, claims processing, provider software, invoicing, and loyalty programs. They offer simplified healthcare transactions for providers and insurers via POS/payment apps, improving the overall experience.


High Availability and Scalability

High Customer Traffic

Mobile-Ready Accessibility

Seamless Mobile Deployment for Accessibility

Multi-Environment Setup and Organizational SLAs

Robust Business Growth Framework

The Challenge

When moving microservices from AWS Elastic Beanstalk to Amazon EKS, the customer encountered cost and scalability issues. Their aim to achieve high availability, auto-scaling, faster feature deployment, account separation, automated CI/CD, efficient troubleshooting, containerization, microservice best practices, performance monitoring, logging, security measures, restricted access, private subnets, IAM roles, and secure authentication for Amazon EKS.


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

The Results

Achieved multi-environment setup, ensured high availability and scalability, and enabled easy mobile deployment for business growth and enhanced customer experience.

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