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Env files aren't meant for storing secrets

Hacker News

Env files aren't meant for storing secrets

I think .env files are fine for non-sensitive config but they’re a terrible place to store real secrets once you have a couple of engineers, machines, or a single engineer with multiple concurrent projects. But I've worked for big and small tech and have seen this happen: 1. .env files are plaintext credential dumps 2. teams share .env files via slack and eventually drifts 3. accidental .env commit I built envmap, a small cli tool that manages and injects your environment key values locally + with support for aws + vault + 1pass backends as source of truth. I use this and deleted my .env, .env.example, .env.production(I'm the worst). Would appreciate any feedback + contributions!

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, slack, single · Missing: agents, macos, agent
88%88% 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 · Strong signals: ide, io · Missing: https docs, excited, just released
47%47% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
29%29% 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
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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