Confidential Computing extends encryption to data in use, protecting sensitive workloads even from cloud infrastructure access.
What is Confidential Computing?
Confidential Computing encrypts data while it is being processed in memory. Traditional cloud security encrypts data at rest (storage) and in transit (network), but data must be decrypted for processing. Confidential VMs use AMD SEV (Secure Encrypted Virtualization) to encrypt the entire VM memory with hardware-managed keys. Even Google operators and the hypervisor cannot access the plaintext data.
Core Features
- Hardware-based encryption: AMD SEV encrypts all VM memory at the CPU level
- Transparent operation: No application changes required for Confidential VMs
- Per-VM isolation: Each VM has unique encryption keys managed by hardware
- Remote attestation: Cryptographically verify that workloads run in genuine confidential environments
- Confidential GKE: Run Kubernetes workloads on confidential nodes
- Confidential Space: Multi-party computation without exposing raw data to any party
Typical Use Cases
Financial Services Data Processing
Banks and financial institutions process sensitive customer data, trading algorithms, and risk models. Confidential Computing ensures this data remains encrypted even during computation, meeting regulatory requirements and protecting intellectual property.
Healthcare Analytics
Healthcare organizations analyze patient data for research and clinical decision support. Confidential Computing allows processing of PHI (Protected Health Information) with additional protection against unauthorized access, supporting HIPAA compliance.
Multi-Party Data Collaboration
Multiple organizations can jointly analyze combined datasets without exposing their raw data to each other. Confidential Space provides a trusted execution environment where computation happens on encrypted data from all parties.
Benefits
- Defense in depth: Adds memory encryption to your security layers
- Regulatory compliance: Demonstrates additional protection for GDPR, HIPAA, and financial regulations
- Reduced insider risk: Data protected even from cloud operator access
- No code changes: Confidential VMs work with existing applications
- Minimal overhead: Only 6-10% performance impact for full memory encryption
Integration with innFactory
As a Google Cloud Partner, innFactory helps you implement Confidential Computing for sensitive workloads. We assess which applications benefit most from confidential environments, design architectures that leverage Confidential VMs and GKE, and help you demonstrate compliance with regulatory requirements.
Available Tiers & Options
Confidential VMs (AMD SEV)
- No code changes required
- Full VM memory encryption
- ~6% performance overhead
- N2D machine types only
Confidential GKE Nodes
- Kubernetes-native integration
- Node-level encryption
- Works with existing workloads
- Limited to supported node types
Confidential Space
- Multi-party computation
- Attestation-based trust
- Data clean rooms
- Requires workload redesign
Typical Use Cases
Technical Specifications
Frequently Asked Questions
What is Confidential Computing?
Confidential Computing encrypts data while it is being processed in memory. Using AMD SEV technology, the entire VM memory is encrypted with hardware-managed keys that even Google cannot access. This protects against memory attacks and insider threats.
How much performance overhead does Confidential Computing add?
Confidential VMs typically add 6-10% performance overhead compared to standard VMs. The overhead comes from memory encryption/decryption operations. For most workloads, this is negligible compared to the security benefits.
Do I need to modify my applications?
No. Confidential VMs are transparent to applications. You select a Confidential VM machine type, and the memory encryption happens automatically at the hardware level. Existing applications run without code changes.
Which machine types support Confidential Computing?
Confidential VMs require N2D machine types with AMD EPYC processors. These are available in sizes from n2d-standard-2 to n2d-standard-224. Confidential GKE uses the same underlying machine types for worker nodes.
How does Confidential Computing differ from encryption at rest?
Encryption at rest protects stored data. Encryption in transit protects network data. Confidential Computing protects data during processing: the memory where your application runs. Together, they provide complete data lifecycle protection.
