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Load Testing with Playwright

Hacker News

Load Testing with Playwright

Hi HN fam! Hassy from Artillery (YC S21) here. Playwright got a lot of love on HN today [1] - rightfully so, it's an incredible project! - so I thought I'd resubmit [2] an open-source project that lets you run load tests with existing Playwright scripts. GitHub link: https://github.com/artilleryio/artillery-engine-playwright The basic motivation for creating the project is that load testing complex web apps is a real pain in the ass. It takes ages to build out test scripts for a non-trivial web app with traditional API-oriented tools. If you've ever had to do it, you know how frustrating it can be. So we thought, why not try load testing with real browsers instead? Especially if we can just reuse existing E2E testing scripts we already have? (based on Playwright of course!) Turns out it can work very well. Is load testing with real browsers expensive? Yes, sort of - relative to more traditional load testing. This project lets you max out developer productivity points at the cost of... well, cost. But! developer time is expensive! And cloud compute is cheap - running 1,000 4 vCPU/12GB RAM containers on AWS Fargate for an entire hour is going to cost ~$220 in Fargate fees for example. The project is still in its early days, would love any feedback! <3 1. https://news.ycombinator.com/item?id=30083042 2. https://news.ycombinator.com/item?id=29402399

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
90%90% 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: apps, new, open · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, 000 · Missing: https docs, excited, just released
75%75% predicted probability of success on Hacker News, based on ML models trained on real launch data.
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36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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