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I made desktop app to browse and reduce AWS cloud costs

Hacker News

I made desktop app to browse and reduce AWS cloud costs

I made CloudPouch application to help individual engineers or architects to understand and reduce AWS costs. I have already earned few hundred bucks on it, and decided to spend it on explainer video that is provided in the link. I hope you like it. Here are several facts that make CloudPouch unique: 1. It is a desktop application, not SaaS. Thus, you don't need to share your cost data with my company. The application connects directly to AWS from your computer, without anything in a middle. 2. Since that, you don't need any special approvals from management to use it, as you don't share sensitive information with any 3-rd party. All you need is ce:GetCostAndUsage privilege to access cost data. This is standard IAM action, that many engineers already have access to. 3. There is no red tape. That's why you can use it with all AWS accounts to which you already have programmatic access. CloudPouch loads your AWS CLI and SSO profiles that you already have defined on your computer. Without any additional configuration. This is super handy! 4. It saves a lot of time because you can switch between different accounts inside the CloudPouch application. You don't need to login into the AWS web console, deal with multiple browser windows, and all that hassle. I overlook many accounts. I can use it with all of them. 5. It shows cost data in a predefined way. That means that billing data from any of your accounts will be displayed in the same, familiar way. Even BETWEEN accounts belonging to different customers of yours. This makes you more productive! 6. It's cost-effective. A single license costs $10 per month, regardless of: - the number of AWS accounts you use, - the bill size on each of them. This makes it a superb choice for any cloud consultant, architect, or engineer. 7. It works on macOS, Windows, and Linux, and is really fast! https://cloudpouch.dev/ I'm looking for your feedback and ideas how to make it more useful for AWS users.

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, user · Missing: agents, agent, cursor
83%83% 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 · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, month, users · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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 · 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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