Enhancing Platform Stability and Performance through Automated and Manual Testing Framework

The client faces increasing difficulties managing vast data volumes, complex integrations, and maintaining platform stability during high-traffic scenarios. Pre-implementation, issues included intermittent failures, inaccurate retailer data ingestion, and quality control lapses amid rapid deployment cycles, affecting user experience and trust.

A large-scale online retail aggregation platform that consolidates product data from multiple retailers to provide seamless search and comparison experiences to consumers and retailers.

• Reduce the number of user-reported bugs post-deployment.
• Increase system uptime to above 99.99%.
• Enhance platform performance to effectively handle traffic spikes without degradation.
• Improve accuracy and synchronization of retailer data feeds to boost user confidence.
• Implement rigorous testing processes integrating manual and automated techniques to facilitate faster, reliable releases.

• Manual exploratory testing protocols to identify UI issues, broken links, and usability flaws.
• Usability validation modules to review site navigation and checkout flow consistency.
• Retailer feed validation processes to verify accuracy of catalog updates post-ETL, including descriptions, prices, and availability.
• Automated test scripts to simulate user journeys such as product search, filtering, and visual search, covering approximately 900 verification points with execute times around 45 minutes for full end-to-end runs, performed twice daily.
• Automated API testing for internal services, deploying full regression suites on five key APIs with continuous execution upon code changes.
• Automated performance testing to simulate traffic spikes, identify bottlenecks, and optimize infrastructure—using iterative testing to refine system response times and stability.
• Real-time monitoring automation via CI/CD pipelines to detect, report, and resolve issues proactively.

• Retailer product data feeds for validation
• Internal APIs for critical functionality testing
• Monitoring systems for real-time performance and health metrics

• System uptime target ≥ 99.99%
• Automated tests covering critical user flows with execution times under 45 minutes for comprehensive end-to-end runs
• Frequent, automated execution of testing workflows aligning with continuous deployment cycles
• Scalable infrastructure supporting traffic spikes and load testing results
• Secure handling of retailer data feeds and user information

The project aims to achieve a substantial reduction in user-reported bugs, increasing platform uptime to over 99.99%. It will ensure faster, more reliable deployment cycles, improve data accuracy and synchronization, and enhance overall user experience and confidence. These improvements are projected to support higher traffic volumes, foster retailer trust, and solidify the platform's reputation as a stable, high-performance solution.