Op

Open-Source Rego Policy Enforcer for Open-Policy Agent(OPA)

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Open-Source Rego Policy Enforcer for Open-Policy Agent(OPA)

Hey everyone, I'm one of the co-founders of Permify. We're building open-source authorizations for better fine-grained systems. We recently build Rego policy enforcer. It's an open source tool that allows you easily create complex authorization policies. Supports RBAC, ABAC and resource filtering based on them. You can basically; - Generate your complex authorization policy easily with code. - Export the rego (policy language for defining rules that are evaluated by the OPA engine) you created with the code. - Filter data based on your authorization logic. - Make decisions about multiple resources from one policy. - Get the details of the decisions made. - Add custom messages and handle decision messages. Looking forward hear your feedback :)

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, code, open · Missing: mac, agents, macos
85%85% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: supports, created · Missing: reddit linkedin, podcasting, latex
57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, open source, io · Missing: https docs, excited, just released
48%48% 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 · 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 · Missing: plus, platform, intuitive
27%27% 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
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.

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