Kamal Handbook, 2nd Edition

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Hi fellow readers of HN, I made a new edition of Kamal Handbook to address the big leap of changes from Kamal 2. A lot had to be rewritten and I made the book even a bit longer and better as much as I could. Kamal is an imperative deployment tool. It's basically a successor to Capistrano, but for a container era. Kamal 2 is solving the main painpoints people had with version 1: - auto SSL for single-server deployments - multiple apps on a single-server - unifying ENV management with 'kamal deploy' - faster deploys I really believe that Kamal is now a better option than Docker Compose or Dokku, perhaps even than Kubernetes (use-case provided). Compared to my previous HN announcement of the first edition mentioning 300 sales, I now crossed 1000+ sales on Gumroad. I cut a new preview for SHOW HN again here: https://kamalmanual.com/handbook/first-deploy-preview.pdf Josef

Visit product View on Hacker NewsNov 18, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: apps, dock, new · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released

54%54% 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: apps · Missing: mobile apps, ios, personal

40%40% 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

30%30% 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

15%15% 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.

Incorrect prediction on native model

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