CASE STUDY • Data Extraction & Scraping
Resilient Web Scraping Engine for Market Telemetry
Enterprise Market Intelligence Firm tracking daily pricing and availability signals across global retail platforms.
System Uptime
99.4%
Maintained over 12 consecutive months
Daily Price Signals
1.2M
Clean structured data payloads extracted
Extraction Cost
45% ↓
Optimized headless browser lifecycle
The Problem & Anti-Bot Obstacles
Target e-commerce platforms aggressively altered HTML structures and engaged bot protection (Cloudflare, Akamai, PerimeterX), resulting in ~60% daily execution failure for traditional scraping scripts.
IMPACT: Broken data feeds corrupted daily market pricing models, causing client telemetry updates to go dark for days at a time.
System Architecture & Engineering
Deployed a distributed cluster of headless Playwright browsers with dynamic proxy rotation, visual state inspection, dynamic DOM wait patterns, and automated structural DOM repair.
Implementation Highlights
- ▪Headless Playwright cluster managed via Kubernetes worker nodes.
- ▪Automated proxy pool health check and rotation.
- ▪Pydantic response schema verification to detect stealth anti-bot blocks.
- ▪Automated fallback parsing using vision-LLM for modified layouts.
TECH STACK USED
PlaywrightPythonFastAPIRedis QueuePandasPostgreSQL