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Reproducible development environments using starlark, without Nix

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Reproducible development environments using starlark, without Nix

Hi all, I'm the maintainer of https://github.com/kubeflow and https://github.com/tensorchord/envd . I've been part of the kubeflow community for ~5 years. One of the hardest issues I have faced is keeping our development environments in sync. We are often eager to do something speedily on the cloud or debug independently on the MacBooks. This is where envd comes in. It's a command-line utility that helps you create and manage development environments locally, or in the cloud. I can't wait to see what you create with envd. Looking forward to your feedback and contributions to our project. Happy coding!

Visit productView on Hacker NewsNov 25, 2022
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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, using, coding · Missing: agents, macos, agent
63%63% 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 NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
51%51% 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
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
42%42% 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
40%40% 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
13%13% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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