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Enhancing Platform Stability and Performance through Hybrid QA Testing Framework
  1. case
  2. Enhancing Platform Stability and Performance through Hybrid QA Testing Framework

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Enhancing Platform Stability and Performance through Hybrid QA Testing Framework

99x.io
eCommerce
Retail
Information technology

Platform Instability and Quality Assurance Challenges

The platform experiences intermittent failures during traffic spikes, inaccurate product listings due to flawed retailer data ingestion, and quality control gaps in continuous delivery processes. These issues compromise user experience, erode retailer trust, and hinder the platform's ability to scale effectively in a growing market.

About the Client

Digital marketplace aggregating furniture products from multiple retailers into a unified search and comparison platform

Key Project Goals

  • Implement hybrid manual/automated testing framework
  • Achieve 99.99% platform uptime
  • Reduce production bugs by 90%
  • Ensure 100% accurate product data ingestion
  • Optimize performance under high-traffic conditions

Core System Requirements

  • Exploratory testing for UI/UX validation
  • Automated end-to-end test scripts for critical flows
  • API integration testing framework
  • Performance stress-testing capabilities
  • Real-time monitoring and alert system
  • Automated ETL validation for product data

Technology Stack Requirements

JavaScript/TypeScript
Cypress
Cucumber
SpecFlow
Jest with Supertest
Grafana K6
Azure
Kubernetes
SQL Server
Cosmos DB

System Integration Needs

  • Retailer inventory APIs
  • ETL data pipelines
  • GitHub workflow automation
  • Monitoring dashboards (Grafana)
  • Cloud infrastructure (Azure)

Non-Functional Requirements

  • Support 10,000+ concurrent users
  • 99.99% system availability SLA
  • 45-minute test suite execution SLA
  • Real-time error detection and reporting
  • Scalable infrastructure for traffic spikes

Expected Business Impact

Implementation of the hybrid QA framework will reduce production incidents by 90%, improve deployment confidence through automated validation, and ensure accurate product data representation across 100% of retailer integrations. The platform will achieve enterprise-grade reliability with 99.99% uptime, supporting 300% traffic growth capacity while maintaining sub-2s page load times during peak usage periods.

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