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StackOps – an AWS CloudFormation deployment pipeline and console

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StackOps – an AWS CloudFormation deployment pipeline and console

After being frustrated with the current crop of Infrastructure as Code tools, I wrote StackOps. It does multi-account CloudFormation deployments and has automatic Stack dependencies with deep links into AWS console. StackOps setup in your AWS account takes less than 5 minutes. Free to try. For AWS Solutions Architects and DevOps engineers wanting to begin their Infrastructure as Code journey. Great for small or large enterprises. Need help? I'd love to get on line with you and step you through things. Audio overview available on StackOps home page - click the orange talking heads on the right.

Visit productView on Hacker NewsNov 29, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos
69%69% 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: pipe, io · Missing: https docs, excited, just released
57%57% 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
46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
20%20% 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
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · 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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