React SaaS – Boilerplate with automated setup of dev/prod environments

Hacker News

After accidentally nuking the production database of my last side project, I wished I had used dev/prod environments with automated DB backups. When I looked for a SaaS template to start over with integrated dev/prod environments, I couldn’t find one. So I decided to build it myself. To help speed up the setup, I also built Bash and PowerShell scripts to guide users through the process. The current stack is Next.js, Firebase, and Stripe. However, I’m considering writing some Terraform modules for GCP resources to further speed up setup and provide more flexibility for power users. Would love to get your feedback!

Visit product View on Hacker NewsSep 16, 2024

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

73%73% 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

64%64% 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

41%41% 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

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

18%18% 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

1%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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