Carolina Cloud – the farm-to-table of cloud computing

Hacker News

We were getting smashed with AWS bills and despite not having much background in it, realized that assembling our own hardware is about the same as 1-3 months of renting it on AWS. It was a no-brainer to build our own. We since started expanding to friends and family, and are proud to report we've saved several small businesses massive amounts of money. We are based in North Carolina with latency to us-east-1 of less than 8ms. We have had 99.99% uptime over the past year. And we charge between 1/3 and 1/2 of an equivalent AWS machine (usually closer to 1/3) while offering a 300% refund for any downtime. We are not the best fit for mission-critical things like consumer banking apps, FedNow or the Instagram backend, but we're perfect for things like high RAM instances for data science experimentation, getting your feet wet with GPUs and CUDA and hosting a RAM-intensive backend for your iOS app or Chrome Extension. We also offer direct phone support...we have backgrounds in finance, software engineering and data centers ourselves so we'd love to help you strategize. Oh yeah, and we have GPUs.

Visit product View on Hacker NewsMay 27, 2025

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

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, month · Missing: mobile apps, personal, entrepreneurs

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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

24%24% 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.

Incorrect prediction on native model

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