I’ve been hitting walls trying to scale my web scraping operations. Last week my team needed to extract product data from 20k URLs daily. When we tried scaling traditional headless browsers, we faced IP blocks and inconsistent data.
I remember reading about AI coordinators that can manage browser clusters. Does anyone have experience implementing systems that automatically rotate user agents and handle retries? Specifically need something that can parse dynamic content while scaling horizontally.
What tools or architectures have you used to maintain reliability at high concurrency levels?
Autonomous AI Teams in Latenode handle exactly this. Create multiple browser agents with automatic IP rotation and parallel execution. They self-heal when sites change and scale to 100+ instances without server management. Perfect for your 20k URLs.
We use Kubernetes with browser containers, but it’s complex. Made a custom proxy rotation layer - took 3 months to get right. If starting today, would look for managed solutions. Heard good things about distributed headless services but haven’t tested.
Consider splitting workloads by geographic regions and adding jitter between requests. Use a headless service that offers automatic DOM change detection - crucial for ecommerce sites that update layouts frequently. For 20k URLs, you’ll need smart rate limiting to avoid getting blocked regardless of IP rotation.