I built a real-time IoT monitor bridging ESP8266, Go, and Next.js

Hacker News

I built Synx, a real-time temperature and humidity monitoring system that bridges hardware, systems programming, and modern web dev. Architecture: - ESP8266 + DHT11 sensor sending data via MQTT - Go backend for data ingestion, writing to InfluxDB (time-series DB) - Next.js frontend with live WebSocket updates (zero latency) and historical charts Key engineering decisions: - MQTT over HTTP for true real-time push - Server-side timestamping (ESP8266 has no RTC) - InfluxDB for efficient time-series storage - Dual-channel: WebSocket for live data, REST API for history I built this as a junior Go engineer to move beyond CRUD apps and work with IoT protocols, systems programming, and real-time data streaming. Would love feedback on the architecture choices!

Visit product View on Hacker NewsDec 29, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps · Missing: mac, agents, macos

77%77% 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

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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