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Dead-simple DNS client and ronin that manages /etc./hosts

Hacker News

Dead-simple DNS client and ronin that manages /etc./hosts

Today I've implemented a little DNS client that can act as a DNS ronin, because I didn't have my own resolver running while being on the go. I'm using it to manage my /etc/hosts entries, so that my stupid Web Browser doesn't do DNS queries all the time when the tracking ISP's TTL responses are always set to 0. Anyways, it's implemented in pure go, and has its own code to parse the DNS UDP/TCP/TLS network packets. Thought I might share and it might be interesting to read for others.

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, code · Missing: mac, agents, macos
66%66% 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.
Hacker NewsMay not resonate with HN audience · 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.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
41%41% 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
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
15%15% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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