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Please stress test this demo

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Please stress test this demo

I want to see how many browsers it can run before it becomes unresponsive. It's an 80 core 400 GB Skylake GCP instance running in Oregon. Logically it should be able to run 80 to 160, but at peak usage of around 60 I only saw about 5% utilization. Stress test rules are you can't use a bot or script to do it, it has to be legitimate use to get an idea of what real peak looks like with websocket, browsing websites, bandwidth etc. also running CPU workloads in JS won't work because the monitoring scripts will kill those users. demo at https://start.cloudbrowser.xyz/?stresstest

Visit productView on Hacker NewsJul 28, 2020
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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