Case Study #1

Marketing Automation Platform

Migration and Modernization on AWS

Overview

GrowAasan provides a SaaS platform, a marketing automation tool that manages the complete lifecycle of a customer journey. The solution includes Facebook, Instagram, Google Ads, and review integration. It connects these leads via Verified WhatsApp to make customers easily reachable for conversion.

Business Challenges

  • Limitation of current architecture with respect to scaling and high availability.
  • High re-engineering cost and upfront cost for high availability solutions without assured return.
  • Non-standard infrastructure elements due to unplanned procurement.
  • Higher operational cost and lagging behind the market in terms of technology and process.
  • Millions of rows to be updated every 4 hours.

AWS Services Used

EC2RDS AuroraS3AutoscalingCodeBuildCodeDeployCodePipeline

Offering

Implementation of AWS cloud infrastructure

Implementation

  • Leveraged AWS EC2 across two Availability Zones with Application Load Balancer to run the application with fault tolerance and high availability.
  • Used EC2 Auto Scaling feature to scale the application server for on-demand traffic.
  • Implemented AWS RDS Aurora cluster to handle the update of millions of rows efficiently while reducing costs.
  • Applied AWS Web Application Firewall to protect the web application from OWASP Top 10 vulnerabilities and common web exploits like SQL Injection and Cross-site scripting (XSS).
  • Used AWS CloudWatch to monitor and scale based on CPU and Memory Utilization.
  • Leveraged AWS System Manager for secure login, remote command execution, centralized inventory, and seamless OS patch management.

Key Benefits

  • High performance and Elastic Compute Service enabled scaling up and down capacity as per application performance and architecture needs.
  • Increased high availability, flexibility, and cost reduction.
  • A cloud-native monitoring system with performance insights.
  • A dynamically scalable solution with minimal operational overheads.