Overview
A leading US-based CRM provider faced a critical hurdle during its infrastructure modernization. To improve scalability, they needed to migrate from multiple individual code droplets to a multi-tenant architecture on AWS. However, the transition was high-risk. The platform lacked existing test documentation, and the migration timeline was aggressive. SourceFuse was engaged to validate the new architecture, ensure strict data isolation between tenants, and certify over 2,000 regression scenarios without delaying the launch.
The Challenge
The client’s legacy setup was inefficient, with separate codebases for different customers. Transitioning to a unified multi-tenant model presented several critical challenges:
- No Test Artifacts: The project started with zero test cases and no functional documentation.
- Large System, Tight Timeline: The team had to migrate a complex CRM application quickly.
- Continuous Regression Needed: Thousands of scenarios required repeated testing to prevent defects.
- Tenant Isolation: Each tenant had to remain completely isolated, adding complexity.
The Solution
SourceFuse implemented an AI-driven Quality Engineering strategy to automate the migration’s success:
1. AI-Assisted Scripting
We used MCP and GitHub Copilot to analyze the codebase and automatically generate test scripts directly from user stories, slashing manual drafting time.
2. Self-Healing Automation
We deployed our proprietary AI Healer (Selenium-Java), which automatically detects UI changes and updates locators, ensuring scripts remain resilient and functional.
3. Smart Data Generation
AI models generated tenant-specific datasets to rigorously test data isolation and multi-tenant security.
4. ML-Powered Analysis
Machine learning algorithms were used to analyze test failures, instantly distinguishing between genuine defects and “flaky” environment issues to speed up debugging.
5. Shift-Left Security
Integrated automated performance and security testing early in the CI/CD pipeline to catch vulnerabilities before deployment.
Results
SourceFuse delivered a seamless migration and transformation:
- 30–40% efforts savings in test design and execution.
- Zero defects reached production.
- Migration completed quickly and confidently.
- The platform now scales on demand with a robust multi‑tenant architecture.
Technologies & AWS Services Used
- Compute: Amazon EC2
- CI/CD: AWS CodePipeline, AWS CodeBuild
- Security: AWS Identity and Access Management (IAM), Amazon Inspector
- Database: Amazon RDS (Multi-tenant validation)
- Monitoring: Amazon CloudWatch
- AI Tools: GitHub Copilot, Model Context Protocol (MCP), ArcMod.ai
- Automation Framework: Selenium-Java with In-house AI Healer
- Environment: Multi-tenant AWS Architecture
- Management: Jira Integration for automated test mapping
