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A Platform to Practice AWS+Terraform
Hacker NewsA Platform to Practice AWS+Terraform
I built this because I like learning infrastructure with Terraform. Things like provisioning an EC2 instance with SSH may look simple on the console since it's just checking a checkbox, but in Terraform, this requires users knowing a lot more concepts, which I see as an alternative way for hands-on learning. There are currently 54 questions regarding AWS+Terraform on the platform. No AWS accounts are required from users. I'd appreciate your feedback!
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Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos74%74% 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: io · Missing: https docs, excited, just released60%60% 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, podcasting53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal47%47% 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, revenue13%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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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