When I first got into web scraping, I assumed proxies were a solved problem.
Pick a provider, rotate IPs, done.
That turned out to be completely wrong.
The real problem
What surprised me the most wasn’t how to scrape data — it was how difficult it was to keep scraping consistently without getting blocked.
Even with rotating proxies, I kept running into:
- sudden drops in success rate
- inconsistent performance
- random blocks after scaling up
At first I thought it was just bad implementation. But after testing different setups, it became clear that the proxy layer itself plays a much bigger role than I expected.
What actually made a difference
After trying multiple approaches, a few things stood out:
- IP quality matters more than quantity
- not all proxy networks behave the same under load
- rotation strategy matters more than “rotate everything”
One of the biggest differences I saw was between datacenter and residential IPs.
Why residential proxies changed things
Once I switched to residential proxies, the stability improved noticeably.
Requests blended in better, sessions lasted longer, and overall success rates were much more predictable.
It’s not perfect, but it’s a completely different baseline.
Comparing providers is harder than it should be
Another challenge was figuring out which provider to actually use.
Most sites just repeat the same claims:
- largest IP pool
- best performance
- highest success rate
But those don’t mean much without context.
I ended up putting together a simple comparison for myself just to make sense of the differences:
https://openwebdata.io/
Nothing fancy, just a way to compare things like performance, IP pool size and stability side by side.
Final thought
If you're working on scraping or data collection, the proxy setup is not something you can treat as an afterthought.
Understanding how it behaves under real conditions is what makes the difference between something that works occasionally and something you can rely on.
Top comments (0)