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PulseGrid – real-time monitoring in C++

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PulseGrid – real-time monitoring in C++

I built a small production monitoring system in C++ to explore what a modern backend runtime could look like without heavy frameworks. It monitors HTTP endpoints, tracks uptime and latency, and streams updates via WebSocket. The goal was to keep the system simple and understandable, with a clear architecture: domain -> application -> infrastructure -> presentation It runs on a low-cost VPS and handles real traffic. This is powered by Vix.cpp: https://github.com/vixcpp/vix Source code: https://github.com/GaspardKirira/PulseGrid I’d appreciate any feedback, especially on architecture and design decisions.

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Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos
71%71% 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
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
48%48% 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 · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% 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
19%19% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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