From Legacy to
Cloud Velocity.
We migrated a complex R&D legacy system to a serverless Azure architecture, cutting costs by 66% while unlocking real-time analytics.
Microsoft Azure
Python
Django
Problem Statement
Migration of a legacy R&D application to Azure cloud with all master & legacy data, along with reports, to build enhancements into the tool for seamless analysis of data.
Legacy Constraints
- Old technical stack limiting scalability and innovation.
- Complexity in data gathering with strict confidentiality needs.
- High maintenance costs ($30k/year) and risk of server failure.
Serverless Architecture
- Serverless Design: Reduced development and run costs significantly using Azure functions.
- Custom Dashboards: Improved visibility with real-time experiment tracking and reporting.
- Robust Security: Role-based access control (RBAC) to manage sensitive experiment data securely.
Key Benefits
Delivering tangible business value.
Azure Storage Scalability
Ensures efficient data management and storage, guaranteeing optimal performance even as data loads increase.
Web Apps Scalability
Offers vertical & horizontal flexibility to adjust resources based on user traffic, ensuring a seamless experience.
Auto-Scaling Mechanism
Optimizes resource utilization and cost-effectiveness, making the solution economically sustainable.
"AudvikLabs played a crucial role in transforming our legacy applications through their cutting-edge cloud solution, empowering us to achieve unparalleled productivity and efficiency through seamless migration and innovative technology."