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PerfAgents – Find Issues Before Your Users Do with Synthetic Monitoring

Hacker News

PerfAgents – Find Issues Before Your Users Do with Synthetic Monitoring

Hello HN! We’re excited to share PerfAgents, a synthetic monitoring tool built for startups and enterprises seeking robust and proactive monitoring across global regions. TL;DR: PerfAgents is a synthetic monitoring platform that uses your existing E2E automation scripts (Playwright, Puppeteer, Cypress, and Selenium) for web app monitoring, reducing setup time by 80%. No complex integrations, no vendor lock-in, and proactive alerts that let you catch bugs before users do. Problem We’re Solving: Ensuring application reliability across all regions is tough, especially when existing monitoring tools either require extensive DevOps/QA setup or lock users into proprietary workflows. This results in inefficient workflows, delayed issue detection, and, often, user-facing bugs in production environments. How We Solved It: PerfAgents offers a multi-framework approach that lets you monitor app functionality without needing new integrations or script re-recording. By reusing existing end-to-end scripts, PerfAgents makes setup fast, keeps monitoring flexible, and allows teams to detect and resolve issues faster. Features include: -> Multi-framework support for Playwright, Puppeteer, Cypress, and Selenium -> AI-driven monitoring script generation to automate monitoring setups with no code -> Global test execution for instant insights across regions -> Real-time alerts integrated with popular tools (Slack, PagerDuty, Jira) -> Flexible pricing based on execution frequency, not script complexity How It Works: -> Setup: Connect your GitHub repository to import existing scripts, or use our built-in AI tools for zero-code setups. -> Monitor & Alert: Configure regional monitoring and alert channels, with real-time notifications when an issue occurs. -> Optimize & Scale: Review logs, performance reports, and leverage our multi-framework support to refine application flow monitoring. Key Benefits: -> Faster issue resolution: Early detection and instant alerts prevent downtime and improve stability. -> Cross-team collaboration: Centralized data helps DevOps, QA, and product teams collaborate more effectively. -> Flexible framework support: Avoid vendor lock-in with multi-framework compatibility. -> High scalability: Configurable monitoring counts ensure you’re only paying for what you use. PerfAgents is already in use by Fortune 500 companies and has helped SaaS and e-commerce teams reduce downtime by 40% and cut support tickets by nearly 57%. Who It’s For: -> DevOps, QA, and Engineering leaders looking to optimize monitoring setup and execution -> Teams already using frameworks like Playwright, Puppeteer, Cypress, or Selenium -> SaaS and e-commerce platforms where reliable, global user flows are critical PerfAgents is available for a free trial now. We’d love to hear your thoughts, and if you have any questions, feel free to ask!

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, slack · Missing: mac, macos, cursor
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, existing · Missing: https docs, just released, lua
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, efficient, users · Missing: plus, intuitive, reviews
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas, active · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: collaborate · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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