Vyro: AWS Migration

  • Hunain Abbas
Vyro AWS Migration - Rayn

The client is a start-up focused on building AI/ML-powered mobile apps on both Android and IOS which are being used by millions of users worldwide and are gaining more popularity with time by providing amazing tools and features.


The client wanted to build a modern, scalable, well-architected infrastructure to support a fast-growing business.

To achieve its goal of dramatically increasing the customer base, the client needed a modern infrastructure to deliver new features and functionalities rapidly and enhanced scalability to handle increased demand.


The client was running ML workloads on GPU-based GCP instances, but there were performance issues. They were using Nginx for load balancing and there were no autoscaling mechanisms in peak times when traffic suddenly increased, and their applications crashed many times.

AimFit leverages several Amazon Web Services

The client leveraged several Amazon Web Services on the proposal of Rayn, which were

  • Amazon Elastic Container Service (Amazon ECS) A highly scalable, high-performance container orchestration service that supports Docker containers enabled the client to run and scale containerized applications on AWS.
  • Amazon Elastic Container Registry
    A fully-managed Docker Container registry integrated with Amazon ECS made it easy for the client to manage, store and deploy Docker container images.
  • Amazon Virtual Private Cloud (Amazon VPC)
    The Amazon VPC enabled the client to provision a logically isolated section on AWS where they could launch AWS resources in a virtual network that they defined.
  • Amazon Elastic Compute Cloud (Amazon EC2)
    A web service that provides secure, resizable computing capacity in the cloud. It is designed to make web-scale cloud computing easier for developers. It provided complete control of computing resources to the client and ran on Amazon's proven computing environment.
  • AWS Auto Scaling
    This monitored the client’s applications and automatically adjusted capacity to maintain steady, predictable performance at the lowest possible cost.
  • Amazon Route 53
    A highly available and scalable cloud Domain Name System (DNS) web service was provided for a reliable and cost-effective way to route the client’s end users to internet applications.
  • Amazon CloudWatch (CloudWatch)
    This monitored applications, responded to system-wide performance changes, optimized resource utilization, and provided a unified view of operational health to the client. 
  • AWS Application Load Balancer
    This balanced the application load to compute resources and served as the single point of contact for clients.
  • AWS Availability Zone (AWS AZ)
    One or more discrete data centers with redundant power, networking, and connectivity in an AWS Region, enabled the client to operate production applications and databases that were available, fault-tolerant, and more scalable than they would have been from a single data center.
High-level Architecture Diagram

“A reliable system should have a well-planned foundation with scalability to handle changes in demand or requirements.”

AWS Cloud Services, managed by Rayn, have enabled the client to:

Improve reliability and availability

The client now has a reliable and reproducible infrastructure for different environments, saving valuable engineering time. CloudWatch provides alerts on the infrastructure’s health to support reliability. AWS ALB helps improve the reliability and performance efficiency of the AWS environment. Amazon Route 53 provides a highly available public endpoint.

Enhance scalability

Amazon EC2 provides secure, resizable computing capacity. Amazon ECS is a highly scalable, high-performance container orchestration service. AWS ALB helps improve the scalability of the AWS environment.

Save costs and time

Rayn’s broad breadth of DevOps knowledge and cost optimization experience saves the client costs on AWS and speeds their time-to-market.

Share Article

More from our blog

TechUser Research

Tailoring Large Language Models to Specific Domains

March 27, 2024

Haider Ali


Feature Prioritization with RICE

December 26, 2023

Maryam Shah

CultureTechUser Research

Is Digital Transformation Changing the Workplace?

December 12, 2023

Simrah Zafar