The first open-source Infrastructure-as-Code framework

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Hey HN, Zach here, cofounder of Coherence (withcoherence.com). After over two years supporting customers deploying apps to AWS and GCP we’ve come to the conclusion that developers really want to own the customization and configurability that the public cloud provides without having to write and maintain all the glue code that goes with it. That’s why we’re launching CNC ( https://github.com/coherenceplatform/cnc ), an open-source framework that equips developers with the right tools to deploy applications with precision. Rooted in the principles of Infrastructure as Code (IaC) using terraform, cnc translates high level service definitions into reference architecture based infrastructure across various environments — whether it’s for development, staging, production, or ephemeral environments. For those who have used AWS's Amplify CLI, think of cnc as a broader, adaptable framework that supports your unique deployment needs. Check it out and please contribute. We’re excited to see how this project evolves.

Visit product View on Hacker NewsJul 18, 2024

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Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

83%83% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

22%22% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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