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Screen record cloud console tasks – get IaC

Hacker News

Screen record cloud console tasks – get IaC

Hi HN, people often perform cloud ops via their GUI, but we strongly believe all things should be in IaC. IaC can suck to write, and many people have no idea where to start. Our thoughts were to let users convert screen recordings of cloud GUI actions, like creating an EC2 instance, into documented SOPs to share with teammates, and generating IaC templates to help move those manual actions towards safer, exportable IaC. We think the documentation can be helpful to share with less technical folks who want guides to self-service provisioning, while the IaC can be good starting templates for engineers. Curious on if the documentation piece or IaC generation is helpful. It is in beta and available for free if you have a mac! Would love any and all feedback (esp if you think it sucks), thanks HN :)

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, recordings · Missing: agents, macos, agent
89%89% 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: ide, io · Missing: https docs, excited, just released
70%70% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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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