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Open-Source, Google Zanzibar Inspired Authorization Service

Hacker News

Open-Source, Google Zanzibar Inspired Authorization Service

Hey HN, I recently shared my thoughts on why Google Zanzibar is a great solution for implementing authorization[1] and why we decided to build Warrant’s core authz service using key concepts from the Zanzibar paper. As I mentioned in the post, we recently open sourced the authz service powering our managed cloud service, Warrant Cloud[2], so I thought I’d share it with everyone here. Cheers! [1] https://news.ycombinator.com/item?id=36470943 [2] https://warrant.dev/

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, new, using · Missing: mac, agents, macos
79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
77%77% 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
55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal
51%51% 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
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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