We built a Cloud-Managed Hypervisor to fix running on-prem servers

Hacker News

We’ve been building a Cloud-Managed Hypervisor that makes running applications on your own servers as effortless as the public cloud. Over my career I’ve watched the transition from on-prem to public cloud. The cloud paradigm shift is as much about empowering engineers as it is about elastic infrastructure, but the tooling for on-prem and private clouds is at best heavyweight and at worst stuck in the last century. We've tackled some interesting problems in the process of building this, such as providing a cloud-style metadata service from our platform. We’d love for you to read our story and try it out! Article: https://www.gallium.cloud/story-so-far/ Product Tour: https://www.gallium.cloud/Tour/

Visit product View on Hacker NewsOct 7, 2023

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

73%73% 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 HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

31%31% 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.

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.

Correct prediction on native model

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