Confidential computing makes this possible. It runs code inside secure enclaves, sealing it off from the operating system, cloud provider, and even your own administrators. Paired with multi-cloud architecture, it gives you a way to process sensitive workloads across AWS, Azure, GCP, and beyond—without exposing them to prying eyes.
The old model relied on trusting one provider. That trust is now a single point of failure. Multi-cloud shifts control back to you, spreading workloads across environments to avoid lock-in and reduce risk. Add confidential computing to this, and you gain not just redundancy but true end-to-end protection for workloads in use.
The key is hardware-based. Secure enclaves isolate applications at the processor level. Even root-level access to the host can’t see the data or code inside. This removes entire classes of attack from your threat model, including insider risk and compromised hypervisors.
Encryption for data at rest and in transit is standard practice. But confidential computing brings encryption to data in use. This closes the last gap in the cloud security triad, making multi-cloud deployments safer to operate even in hostile or zero-trust environments.