I’m working on a web scraping project and wanted to improve performance by running multiple Puppeteer instances simultaneously. My approach was to create 4 separate browser pages running in parallel, thinking this would give me roughly 4x the performance boost.
However, when I checked the system resources using process monitoring tools, I noticed the Chrome processes weren’t utilizing full CPU capacity like they did when I ran just a single page instance. The CPU usage was distributed but not maxed out per thread.
I did some performance testing comparing both approaches and surprisingly the single-threaded version actually completed tasks faster than the multi-threaded setup. This was unexpected since I assumed parallel processing would be more efficient.
Am I implementing the multi-threading approach incorrectly? Is there something I’m overlooking in terms of resource allocation or browser configuration? If Puppeteer isn’t ideal for this type of parallel processing, what alternatives would provide better performance for concurrent web automation tasks?
The performance drop you’re seeing happens because Chrome’s process isolation fights against your parallel strategy. Each browser instance you spawn creates its own process tree - separate renderer processes, GPU processes, and network stacks. That overhead usually kills any benefits you’d get from parallelization. I’ve optimized large-scale scraping ops before, and the bottleneck is almost never CPU. It’s network I/O and DOM processing time. Running four browsers at once doesn’t make network requests four times faster - it just creates more context switching and eats up memory. Try using one browser with multiple contexts instead. Browser contexts are lightweight and isolated but share Chrome’s underlying process. Create them with browser.createIncognitoBrowserContext() and they’ll handle cookies and sessions separately while sharing resources more efficiently. If you really need true parallelization, cluster your Node.js app and distribute browser instances across worker processes. You’ll get better resource isolation than cramming multiple browsers into one process.
This is super common with Puppeteer parallelization. Chrome instances share system resources and have throttling that actually hurts performance when you run too many browsers at once. I’ve found the sweet spot is 2-3 browser instances max, not 4. Past that, you get diminishing returns because of memory overhead and Chrome’s resource management. Each browser eats 50-100MB base memory plus extra per page. Try this instead: fewer browsers but multiple pages per browser. Spin up one browser with 2-3 pages and split your scraping tasks across those pages. You’ll get parallelism without the overhead. Also check if the sites you’re scraping have rate limiting or anti-bot stuff - that could be the real slowdown. Sometimes it’s not your code but the servers getting suspicious of multiple requests from the same IP.