AWS Cost-savings tool – open-source

Hacker News

This open-source project helps you save money in ways other than RIs or Savings Plans. It inspects AWS metrics and usage data to find underutilized and unused resources, then visually gives an option to delete, scale down, or optimize those resources. For each resource, it displays the relevant metrics so you can determine whether or not it's truly unused/underused/ It also includes opportunities to save money on different services by enabling native cost savings policies, like S3 retention policies. It runs totally on your computer as an open source project and doesn't send anything back to us. The idea is to give developers a tool to monitor their costs and build cost optimization into their daily workflows. We used these rules internally to cut our AWS bill in half. The package is still young, looking for feedback!

Visit product View on Hacker NewsJul 5, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: computer, visual, open · Missing: mac, agents, macos

86%86% 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.

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

63%63% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% 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

21%21% 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

13%13% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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