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Migration and modernization of boutique technology platform
Customer Success Story

Migration and modernization of boutique technology platform

Migration and modernization of boutique technology platform

Client

A boutique technology start-up revolutionizing the US cannabis sector with a customizable platform designed to empower multi-state operators with innovative tools for market success.

Business Challenge

  • Application Complexity – Services like data hub, consumer app, sync engine, and recommender rely on disparate platforms (ECS, S3, Lambda, Firebase), creating integration challenges.
  • Database Limitations – Aurora MySQL is costly, with security and design inefficiencies impacting performance and compliance.
  • Authentication Control Issues – Lost admin access to Firebase authentication necessitates migration to a secure and manageable solution.
  • Architectural Challenges – Inefficient design with public traffic communication, mixed environments, and S3-hosted web pages hinders scalability and security.

Approach

  • Enhanced RDS Aurora MySQL with schema, index tuning, and version upgrades for performance and cost-efficiency.
  • Data pipeline built on RDS Aurora MySQL for multi-table extraction and processing, automated by Glue triggers.
  • AWS Glue jobs for data extraction, cleaning, and transformation with PySpark, storing processed data in S3.
  • Glue crawlers automate schema discovery and updates in the Glue Data Catalog for efficient querying via Athena.
  • Data encrypted in transit (SSL/TLS) and at rest (SSE-S3 or SSE-KMS), with IAM roles configured for least privilege access.
  • CloudWatch logs capture Glue job execution, and security configurations comply with industry standards with periodic audits.

Technology Components

AWS Services
AWS Glue AWS Identity and Access Management
Monitoring
Amazon CloudWatch
Data Integration
Amazon RDS Aurora
Project Management
Amazon S3 mySQL

Transformational Effects

16%

Faster Query Performance

25%

Reduced CPU Usage

  • 16% Faster Query Performance: Reduced average response times for critical workloads
  • 25% Reduced CPU Usage: Optimized resource utilization during peak hours
  • Enhanced Data Accessibility: Streamlined ETL pipeline for improved analytics and reporting.
  • Cost Efficiency: Leveraged serverless technologies for better performance at lower costs.

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