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I developed a native macOS client for EC2/S3 console

Hacker News

I developed a native macOS client for EC2/S3 console

Hello HN: Here is the link https://apps.apple.com/app/id1579078660 After forgetting to turn off a p2.xlarge instance for a week, I got so mad at myself I learnt swiftUI to build a native macOS console for most of the actions I do on the web AWS console. I didnt want to use electron or other non native frameworks. Most importantly I just wanted it to know how much a certain instance costs right now, no matter its state, its type, its lifecycle(like ondemand or spot) and the costs associated with the EBS volumes attached including their IOPS/throughput and etc. It also has a S3 object browser, and a drag and drop UI to upload your files so that you can make S3 your own personal dropbox. I dont track or store anything, you just query the aws api. Sorry its a paid app, if anyone wants to try it and cant afford it let me know, I can send it to you. I think this can be useful and cost saving for individuals that spend more than 50usd per month on aws.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, apple · Missing: agents, agent, cursor
89%89% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io, including · Missing: https docs, excited, just released
59%59% 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: personal, apps, month · Missing: mobile apps, ios, entrepreneurs
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% 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
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · 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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