AWS, Azure, GCP instance comparison. Region pricing, savings options

Hacker News

Hi I'm Victor, the developer of CloudPrice.net. Over the last 8 months, we've worked hardly to expand our former site, AzurePrice.net, to also support AWS and GCP instances. I would greatly appreciate feedback from the community on what is good or what else might be missing. Below is a quick list of main features that we have: - Single view of all savings options - Metadata about Azure, AWS, GCP instances - Region pricing comparison - Best alternatives (supercharged using ML) - More than 50 filters - Pricing in different currencies - Side by side comparison - Price / Performance - API and batch export of data - Pricing history via API - Unified search

Visit product View on Hacker NewsMar 13, 2024

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

60%60% 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

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

36%36% 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 · Missing: plus, platform, intuitive

33%33% 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

22%22% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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