A Better Alternative to the AWS Console

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Hey HN: Kaveh here, the founder of https://www.usage.ai/ We launched a new free tool to help engineers understand their AWS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up end up becoming cloud accountants or end up forking over a big % of their AWS bill for a tool to understand costs rather than focusing on business problems. Previous to founding Usage, I worked on high-performance computing research at JP Morgan Chase and as a software engineer at a number of smaller startups. Here's how this new tool works: It's fully self-serve and free to use. You connect a limited-access IAM role (read-only + ability to manage RIs and SPs). You'll see cost reduction recommendations on the Recommendations tab, your active and utilization status on the Plans tab, and the ability to splice-and-dice your data on the Instance Search page via Filters. We make money off of a 20% Savings Fee. If you choose not to let Usage optimize your spend, you'll never need to spend money on Usage. Happy to chat directly kaveh@usage.ai Have you experienced any issues with managing your company or organization's AWS expenses? We'd love to hear your feedback and ideas! Blog post: https://blog.usage.ai/new/ Try free: www.usage.ai

Visit product View on Hacker NewsMar 28, 2022

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

85%85% 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

68%68% 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

68%68% 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: way · Missing: mobile apps, ios, personal

42%42% 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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, make money · Missing: web3, crypto, cryptocurrency

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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