Azure Confidential Computing and Zero Trust

Chapter 2. Use Cases and Scenarios

This chapter explores various use cases of confidential computing and how it protects data privacy in different scenarios. These scenarios include the lift and shift of sensitive workloads in regulated industries, sovereign government workloads, data clean rooms, confidential AI, and other use cases.

Lift and Shift

Today’s confidential computing technologies are an enabler for organizations, particularly in highly regulated industries, that want to migrate existing sensitive workloads to the public cloud with minimal effort or add further protection to workloads already running in the public cloud. With VM-level and container-level isolation technologies, organizations can now migrate their most sensitive VM- and container-based workloads to confidential computing-enabled infrastructure with no changes to their code, accelerating the adoption of these technologies.

Sovereign Government Workloads

Governments and public institutions require a high degree of data sovereignty due to the sensitive nature of the data they manage. Moreover, the presence of threats such as insider risk and espionage present substantial hurdles for governments when considering the use of a public cloud, since doing so requires trust in the cloud operator. Confidential computing reduces the need for inherent trust in cloud operators by implementing methods that ensure the protection of both data and code from unauthorized access, even by the cloud operator. Confidential ...