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Comment by winrid | Hacker News Reader

Could be a lot of reasons, but what if you have millions of tags/roles, and a user has a large subset of those roles? This actually happened at one job...

What if you sell reporting on location based data with access control, and customers want fine grain control on who sees what? Then you also can't always use groups. Example: I'm a Healthcare provider with 15k locations. Manager X is responsible for 5k locations, so when we create reports we filter all the data by those 5k locations first. Same with viewing any data in the product.

Just curious how others approached this. You could obviously do grouping somehow.

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I have a similar use case but even worse. Rather than locations users are given access directly to the consumer/patient and the each resource is for some consumer x. So any access not just reporting we have to filter by a huge list of accessible consumers which sometimes can be as small as 50 but large as 100K+ which is massive challenge to scale.

We can obviously manage this still with careful optimization but I'm not sure if this is kind unlimitedly scalable say for 1M+ consumers. I wonder if this can only be handled by reframing business requirements (like location as you are using) or someone has better design/ideas.

Yeah, same problem, but I don't think I ever saw more than 50k resources per user.

I think the best solution potentially is to have the system monitor the "whale" users and have a special case where you turn their list of resources into a single group/tag behind the scenes and add this single identifier to all the relevant objects. It'd be hell to get right and keep consistent but it'd be fast.

It's hard to name things. There's consumers whose data the system records, by resource I meant the data of the consumer (bulk of the system) and obviously users.

The users are authorized on consumer (a set of consumer + a set of roles or action they can do). We have been able to move the role aspect to app layer very cheaply. User A is doing X say running a report, we know role R is needed for it, we then ask the system run the report for the customers user A has access to it with index on consumer for all resources in system allowing fast query. But if your consumer list is too large the efficiency falls.

We can't make auto groups at system level because adding a group column in resource level and updating would be too expensive. There's no just large grouping. Some users say have access to consumer 1..100K where another has random 100K from 1..1M.

Have separate admin-facing and user-facing RBAC. Don't try to force them under one roof. You have an organization, and a product. Both have different authorization needs (many products don't have any), even if they may use the same authentication mechanism.

I tend to keep admin RBAC simple and group-oriented. It's mostly for direct data access permissions (per table, etc), but can add others too. Different groups for different departments. Mainly for internal CRUD apps at first (e.g. Django Admin).

OTOH, User-facing RBAC is project-oriented and uses the virtual policy system described by Tailscale. The users themselves, in a project-manager role, can manage their own policies, memberships, and resources tags. I like to provide sane defaults and support for modifying policies should they even need it. Importantly, one user can have membership in different projects with different roles.

You'd create a project with the 15K resources, add the customer to it in a manager role, and then they choose the policies, tags, and roles to make it work for their organization.

Ofc, admins can also be users. Simply create one or more projects for internal use.

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