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Permify Now Supports Attribute-Based Access Control

Hacker News

Permify Now Supports Attribute-Based Access Control

Hey Everyone, Almost year ago we launched Permify an open-source authorization service to build fine-grained and scalable user permissions and access control systems over here( https://news.ycombinator.com/item?id=32096610 ) My co-founders and I had a enterprise solution agency where we worked with a bunch of fortune 500 companies. Each projects we made we have to re-invent the wheel for access control and authorization. Not having a easy to integrate, scalable and a granular system that can fulfill the requirements of these enterprise companies was a pain in the ass for us. As well as, platform engineers and software architects in these teams as well. So, we start working on a centralized authorization piece which makes authorization less scary for these architects. We learned a lot from google-zanzibar, OPA, and XACML. Yet we wanted make Permify unique. Permify become a true ReBAC system where you can create a structured authorization logic. But there was a missing piece in which makes you build attribute based access rights such as based on date, number of times, amount of money, etc. Today we are launching that piece with Permify ABAC. We would love to get your feedback on this!!! Feel free roast or toast :)

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
88%88% 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: google, user, new · Missing: mac, agents, macos
71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
69%69% 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: google · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
35%35% 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
19%19% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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