CASE STUDY

E-COMMERCE
BLACK FRIDAY
10X TRAFFIC READINESS

FOR AN E-COMMERCE COMPANY

E-COMMERCE PERFORMANCE TESTING
ABOUT CLIENT
ABOUT CLIENT
ABOUT CLIENT
ABOUT CLIENT

E-commerce marketplace ($45M revenue) crashed during previous Black Friday at 3,500 users—6 hours downtime, $780K lost. Projected 40,000+ users for upcoming sale.

The platform required comprehensive performance testing and optimization to handle the massive traffic spike while maintaining zero downtime and optimal user experience.

E-COMMERCE PERFORMANCE TESTING
CHALLENGE
CHALLENGE
CHALLENGE
CHALLENGE
CHALLENGE

Critical issues from previous year's failure:

Previous year: complete crash at 3,500 concurrent users

System failure resulted in 6 hours downtime and $780K in lost revenue.

Marketing projecting 10x traffic spike

Expected 40,000+ users during Black Friday sale, requiring massive scalability improvements.

Unknown performance bottlenecks

No visibility into system limitations causing crashes and failures.

23 microservices with complex interdependencies

Complex architecture requiring comprehensive testing across all services.

Database slow queries and table locks

Performance issues in data layer affecting overall system responsiveness.

CEO mandate: zero downtime required

Business-critical requirement with no tolerance for system failures.

E-COMMERCE PERFORMANCE TESTING
SOLUTION
SOLUTION
SOLUTION
SOLUTION

Implementation

4-person performance engineering team:

Load Testing

Simulated 45,000 concurrent users with realistic shopping behaviors. Traffic patterns matching Black Friday curves. User segments: deal hunters, regular shoppers, mobile/desktop.

Performance Testing

Progressive testing: 5K to 50K users. Breaking point: 8,200 users (identified 9 critical bottlenecks). Tested auto-scaling, CDN, resource utilization.

Optimization

47 database queries optimized (85% faster). Redis caching for catalog, pricing, inventory. Connection pooling, read replicas, async processing. Kubernetes autoscaling with proper thresholds.

Monitoring & Observability

Real-time dashboards (Grafana, Prometheus). Performance alerts and distributed tracing (Jaeger). Incident response runbooks.

Tools

Apache JMeter Gatling Grafana Prometheus Jaeger Redis Kubernetes New Relic Docker
E-COMMERCE PERFORMANCE TESTING
RESULTS
RESULTS
RESULTS
RESULTS
42K+
Concurrent Users Handled
Zero
Downtime During Sale
153%
Revenue Increase YoY
9
Critical Bottlenecks Fixed

Key Achievements:

  • System stable at 42,000+ concurrent users – Platform handled 12x more traffic than previous year's crash point
  • Zero downtime during Black Friday – Flawless performance throughout peak shopping hours with no incidents
  • 153% revenue increase year-over-year – Black Friday sales reached $1.97M compared to $780K previous year
  • Sub-2-second page load times maintained – Average page load time stayed under 2 seconds even during peak traffic
  • 9 critical bottlenecks eliminated – Database queries, caching, and scaling issues resolved before launch
  • Customer satisfaction recovered – Social media sentiment shifted from negative to overwhelmingly positive
  • Ongoing performance improvements – QASolvex continues quarterly load testing to maintain platform readiness
E-COMMERCE PERFORMANCE TESTING
SUMMARY
SUMMARY
SUMMARY
SUMMARY

Business value

  • Performance testing and optimization enabled an e-commerce platform to handle 42,000+ concurrent users during Black Friday
  • Achieved 153% revenue increase year-over-year with zero downtime
  • Transformed platform from failure-prone to highly scalable and reliable

Preparing for High-Traffic Events?

Let's discuss how performance testing can ensure your platform handles peak traffic flawlessly.

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