We’re happy to announce that it is now possible to create database users with privileges scoped to a specific set of clusters or Atlas Data Lakes in a MongoDB Atlas project.

Animation of creating a database user in Atlas restricted to a single cluster

Traditionally, database users have always been created on a project level in Atlas. This provided a centralized interface for database user management as user privileges were scoped to all clusters in your Atlas project. Customers could manage and revoke user permissions confidently, without fear that the updated permissions would be applied to one cluster but not another.

However, this abstraction created limitations for use cases that required creating database users scoped to specific clusters or Data Lakes. After much anticipation, we now offer the flexibility to refine database access on a more granular level.

Restrict database user access to specific Atlas clusters or Data Lakes in a project

Restrict privileges for different environments of the same application

One reason for scoping database users to the resource level is to restrict privileges by environment. For example, you may have a dev cluster, a test/qa cluster, and a prod cluster in the same project, but you don’t want all users to have equal access to all three.

Isolate teams working on different microservices in the same project

Another scenario is to be able to split up users so that certain developers only have access to specific clusters within a project. This is especially useful for customers who have networking restrictions that require them to only use one or two Atlas projects, and therefore co-locate multiple microservices or applications within the same project. With database users per cluster, those customers can now scope team A to only accessing cluster A, and team B to cluster B.

Grant other users to access Atlas Data Lakes for analytics

Finally, this capability also allows admins to restrict a user’s privileges to only Atlas Data Lakes within the project. This is helpful for analysts, data engineers, and other employees who need access to those Data Lakes and not live operational data in a production cluster, for example.

#database

Finer Grained Database User Authorization in MongoDB Atlas
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