Which inline data protection capability allows for the application of granular policies between different instances of the same tenant?

The correct choice concerning inline data protection capabilities that apply granular policies between different instances of the same tenant is data loss prevention. Data loss prevention (DLP) involves a set of technologies and practices designed to ensure that sensitive data is not lost, misused, or accessed by unauthorized users.

In a multi-tenant architecture, DLP solutions can implement policies that specify which data can be shared across different instances while ensuring that sensitive information remains protected. This is particularly important in environments where multiple departments or business units are using the same infrastructure but need to comply with various security and privacy mandates.

While posture management focuses on securing an organization’s devices and network configurations, it does not primarily handle the application of granular policies for data protection between instances. Threat detection is centered around identifying and responding to potential cyber threats rather than enforcing data management policies. Policy enforcement generally refers to the broader application of established security policies across the entire system without the level of granularity needed for specific data protection needs within a multi-tenant setup.

Thus, data loss prevention is the most appropriate and accurate choice for the context of applying granular policies between different instances of the same tenant, targeting the protection of sensitive data effectively.