One of the biggest challenges in large-scale website crawling isn’t crawling itself.
It’s controlling URL explosion.
Modern websites generate URLs endlessly through:
query parameters
faceted filters
sorting systems
session IDs
tracking parameters
pagination combinations
Without strong normalization and prioritization systems, crawlers can waste massive resources analyzing duplicate or low-value pages.
A simple product catalog can suddenly turn into millions of crawlable URL variations.
Some approaches we’ve been experimenting with at WebKernelAI:
URL fingerprinting
parameter normalization
duplicate cluster detection
crawl budget scoring
canonical signal analysis
incremental crawl strategies
What makes this difficult is that every website behaves differently.
A rule that works perfectly for one architecture can accidentally hide important pages on another.
At scale, technical SEO becomes heavily connected to distributed processing, queue systems, and intelligent prioritization rather than simple page scanning.
Curious how others are handling duplicate URL control and crawl budget optimization in large systems.
