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Anti-Detection Architecture: 99.9999% Success Rate for Automotive Scrapers

· 9 min read
Carapis Team
Global Automotive Data Platform

Anti-Detection Architecture: 99.9999% Success Rate for Automotive Scrapers

Modern automotive websites deploy sophisticated bot detection systems—CloudFlare, PerimeterX, DataDome, and custom ML-based solutions. Yet our production anti-detection architecture achieves 99.9999% success rate across 45 million monthly requests to 25+ automotive marketplaces.

This technical deep-dive reveals the exact architecture, code patterns, and strategies that enable enterprise-grade scraping at scale without detection.

API Performance Optimization: Sub-200ms Automotive Data at Scale

· 9 min read
Carapis Team
Global Automotive Data Platform

API Performance Optimization: Sub-200ms Automotive Data at Scale

Serving 50 million monthly API requests for automotive data requires ruthless optimization. Our production API achieves p95 response times of 185ms while handling 5.8M daily requests—a 92% improvement from the initial 2.3-second average.

This technical deep-dive reveals the exact optimizations, architecture decisions, and code patterns that transformed a slow prototype into an enterprise-grade automotive data API.

Real-Time Automotive Data Pipeline: 8,000 Listings/Minute at Scale

· 5 min read
Carapis Team
Global Automotive Data Platform

Real-Time Automotive Data Pipeline: 8,000 Listings/Minute at Scale

Processing 12 million daily automotive events requires bulletproof stream processing architecture. Our production pipeline handles 8,000 vehicle listings per minute with <2-second end-to-end latency—from extraction to searchable database.

This guide reveals the exact distributed systems patterns, Kafka configurations, and processing strategies that power real-time automotive market intelligence.