HealthTech Transformation: How Modernizing Applications Enhanced Performance by 20%
Healthcare Application ModernizationBusiness Impacts
Slashed platform maintenance costs by 30%
Enhanced performance by 20%
Ensured zero downtime during the migration
Customer Key Facts
- Country : USA
- Industry : Healthcare
Problem Context
Our client, a pioneering health tech company, serves over 14 million users with 10,000+ digital workouts across 15+ fitness categories using cutting-edge deep-learning AI. However, acquiring a business operating on AWS created a split environment between AWS and Google Cloud. This dual-cloud setup led to increased expenses and operational complexities, creating data silos and inefficiencies that hindered integration and streamlined operations.
Fragmented data management across the two cloud providers complicated analysis and integration, obstructing seamless data flow and a unified operational view. The split environment also increased the risk of service disruptions, complicating consistent performance and reliability, and negatively impacting the user experience.
Further, escalating costs from maintaining two platforms strained the budget, making platform maintenance unsustainable. As the company scaled, these growing expenses and inefficiencies underscored the urgent need for a strategic solution to optimize operations and reduce costs.
Challenges
- Multi-Cloud Environment: Managing data silos across various cloud providers hindered effective data analysis, increased complexity and costs, creating skill and maintenance challenges.
- High Maintenance Costs: Existing infrastructure incurred substantial maintenance expenses, limiting the ability to invest in growth initiatives.
- Complex Container: Difficulty maintaining the Node.js container due to the integration of an in-house developed Python application and its libraries.
- User Experience Limitations: Performance bottlenecks and system instability were impacting user satisfaction and customer retention.
Technologies Used
Elasticsearch cloud
Google Kubernetes Engine
Google Cloud Storage
Cloud CDN
Node.JS
Postman
Cloud Armor
Cloud load balancing
Cloud Logging
Solution
- Infrastructure setup:
Quantiphi established a secure landing zone on Google Cloud to support future growth.- Automated the generation of CI/CD pipelines for both application and infrastructure deployments using GitHub Actions, facilitating seamless end-to-end delivery.
- Leveraged a Terraform Code Debugger to identify and fix errors in Terraform scripts, saving developers time and streamlining the debugging process.
- Employed Codeaira, Quantiphi's Gen AI-powered Migration Productivity Suite of Accelerators, to auto-document in Terraform scripts, ensuring high-quality, maintainable code.
- Application Refactoring & Data Migration:
Quantiphi improved application performance and scalability through key component refactoring. CodeAira’s MigrationQraft-Code Converter enabled the smooth conversion of Snowflake queries to BigQuery, and we migrated data to BigQuery, unifying data management and eliminating silos. This integration enhanced data accessibility and decision-making. - Modernized Application:
The application was deployed on Google Kubernetes Engine (GKE) to boost scalability and performance. Elastic Cloud integration secured sensitive data, ensuring compliance with industry standards. This modernization improved application reliability, security, and readiness for future demands.
Results
-
Rapid Time-to-Value:
Successful migration in just 5 months, surpassing the initial 8-month estimate and empowering the client to introduce new features faster. -
Significant Cost Savings:
Enhanced cost efficiency, empowering the client to advance incremental development and transfer more applications to Google Cloud. -
Enhanced User Experience:
Improved application performance and reliability have led to increased user engagement and loyalty.
