Draw the Line Around Your Data. Then Enforce It.

A data perimeter is a set of controls that defines which principals can access your data, from which networks, and through which services, enforced at the organizational level rather than resource by resource. It's one of the highest-impact architectural controls you can deploy, and also one of the hardest to implement correctly. On AWS alone, a complete data perimeter requires coordinated policies across service control policies, resource control policies, VPC endpoint policies, and more, spanning six distinct access patterns, and AWS updates its guidance on an ongoing basis. Most organizations end up with partial coverage and no clear view of where the gaps are.

Native separates intent from implementation. You define what must be true once, and Native compiles that into the correct controls for each provider. The same data perimeter definition produces SCPs and RCPs on AWS, VPC Service Controls on Google Cloud, the right Azure Policy constructs on Azure, and many more, without your team having to understand the differences between them. A single data perimeter can generate dozens of distinct controls on any one provider, which is exactly why separating intent from implementation matters: you express it once, and Native handles the dozens of controls underneath. When you add a new provider, you extend the existing perimeter rather than rebuilding it.

Infrastructure as code and IaC scanning are valuable, and Native works alongside them. But scanning operates at the code layer, and a data perimeter lives at the cloud control plane: direct console access, credential compromise, and lateral movement between accounts all bypass the pipeline entirely. Region restrictions, third-party access boundaries, and environment segmentation aren't established through code at all. Native enforces centrally at the control plane, so coverage doesn't depend on every pipeline being wired up, and it simulates the real-world impact of a proposed perimeter before it goes live.

DSPM and CSPM tools find and classify exposure that already exists: a public bucket, an over-permissioned role, sensitive data in the wrong place. They flag it one resource at a time. A data perimeter works at the level of principles, not resources: you declare that data can't leave a region, that third-party access is blocked except through approved patterns, that AI service calls can't reach regulated data, and Native enforces those conditions through the primitives your providers already ship. Where a scanner flags one exposed resource, then the next, the perimeter closes the whole class at once, and it covers domains a scanner has no equivalent for. Most teams run both: Native prevents the exposure, the scanner catches anything that gets through.