I build a tool to speed up your APIs

Hacker News

Hey HN, I built a tool to easily cache API responses. It was originally built to fix my own problems as my database has always been the bottleneck, and I'm not a devops engineer, so I don't have the skills or time to go in and figure it out to fix it. As my site continue to grow I just kept upgrading my RDS to the next instance up and the bill was just getting out of hand. I needed another solution and that's why I built this. I've been using it internally for the past 6+ months. Just whipped up a home page and some docs to help others that are running into the same issue and need a quick solution. Feel free to give it a go and would love any feedback. Denny

Visit product View on Hacker NewsJun 17, 2024

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

82%82% 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: 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.

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

38%38% 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

31%31% 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

14%14% 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.

Incorrect prediction on native model

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