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Grryno – Game server hosting by the minute

Hacker News

Grryno – Game server hosting by the minute

Hey HN! As far as I can tell https://grryno.com is the first game hosting service that let's you pay for game servers on demand, by the minute, rather than having a monthly subscription. It's still a work in progress but is functional. The reason I'm showing you now is to try to get people using it so I can iterate on user feedback rather than trying to guess what people would want. The only game offered at the moment is Minecraft, but I'm open to adding any suggested game servers, even older or open source games. Name it and I'll see if I can do it. Prices of games will be anywhere from $0.05 to $0.25 per hour, depending on the required resources. Minecraft, for example, is $0.25/h because of it's heavy memory requirements. Other, lighter games, such as Teeworlds, would be about $0.05/h The game servers are run using Amazon AWS services which are managed through a Linode web frontend and backend. I started off with everything on Linode using 4 separate application servers to manage everything. After a suggestion from an old work colleague I made the switch to AWS and Docker which has made things an order of magnitude simpler! I managed to dump about half of my existing codebase and drop all but one application server because of the switch to AWS. I'd love to answer some questions about the tech stack I'm using if anyone's interested. I'd also love to hear opinions on what game servers people would be interested in running. Thanks for reading! Ryan

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, para · Missing: supports, reddit linkedin, podcasting
90%90% 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: user, dock, using · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released
61%61% 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 · Strong signals: month, monthly, para · Missing: mobile apps, ios, personal
47%47% 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
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · 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
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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