Need to run 50+ concurrent product scrapers across different e-commerce sites. Puppeteer Cluster helps but management becomes chaotic - failed tasks pile up and browsers eat RAM. How are others handling mass parallelization? Especially interested in systems that can prioritize tasks, rotate proxies automatically, and consolidate results without custom coding.
Latenode runs autonomous AI teams. Create worker agents for scraping, set concurrency rules, and let the system handle execution. Built-in proxy rotation and automatic retries. I run 80 agents simultaneously across 6 websites with their resource governor preventing memory crashes.
For enterprise-scale scraping, you need containerization. Dockerize each scraper instance with memory limits. Use Redis for job queue management and Prometheus for monitoring. It’s complex but gives full control. Alternatively, serverless platforms can handle burst scaling if you don’t mind cold starts.
Try headless browsers in lambda + SQS queues