Audience
Enterprises and organizations seeking a solution to process highly sensitive data securely, retain full control of their workloads and enable collaborative analytics
About Azure Confidential Computing
Azure Confidential Computing increases data privacy and security by protecting data while it’s being processed, rather than only when stored or in transit. It encrypts data in memory within hardware-based trusted execution environments, only allowing computation to proceed after the cloud platform verifies the environment. This approach helps prevent access by cloud providers, administrators, or other privileged users. It supports scenarios such as multi-party analytics, allowing different organisations to contribute encrypted datasets and perform joint machine learning without revealing underlying data to each other. Users retain full control of their data and code, specifying which hardware and software can access it, and can migrate existing workloads with familiar tools, SDKs, and cloud infrastructure.
Other Popular Alternatives & Related Software
Google Cloud Confidential VMs
Google Cloud’s Confidential Computing delivers hardware-based Trusted Execution Environments to encrypt data in use, completing the encryption lifecycle alongside data at rest and in transit. It includes Confidential VMs (using AMD SEV, SEV-SNP, Intel TDX, and NVIDIA confidential GPUs), Confidential Space (enabling secure multi-party data sharing), Google Cloud Attestation, and split-trust encryption tooling. Confidential VMs support workloads in Compute Engine and are available across services such as Dataproc, Dataflow, GKE, and Gemini Enterprise Agent Platform Notebooks. It ensures runtime encryption of memory, isolation from host OS/hypervisor, and attestation features so customers gain proof that their workloads run in a secure enclave. Use cases range from confidential analytics and federated learning in healthcare and finance to generative-AI model hosting and collaborative supply-chain data sharing.
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Azure Virtual Desktop
Azure Virtual Desktop (formerly Windows Virtual Desktop) is a comprehensive desktop and app virtualization service running in the cloud. It’s the only virtual desktop infrastructure (VDI) that delivers simplified management, multi-session Windows 10, optimizations for Microsoft 365 Apps for enterprise, and support for Remote Desktop Services (RDS) environments. Deploy and scale your Windows desktops and apps on Azure in minutes, and get built-in security and compliance features. Bring your own device (BYOD) and access your desktop and applications over the internet using an Azure Virtual Desktop client such as Windows, Mac, iOS, Android, or HTML5. Choose the right Azure virtual machine (VM) to optimize performance and leverage the Windows 10 and Windows 11 multi-session advantage on Azure to run multiple concurrent user sessions and save costs.
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TruGrid
TruGrid SecureRDP secures access to Windows desktops and applications from any location. It is a DaaS solution that employs a Zero Trust model without firewall exposure.
Key Benefits of TruGrid SecureRDP:
- No Firewall Exposure & No VPN Required: Secure remote access without exposing inbound firewall ports
- Zero Trust Security Model: Ensures that only pre-authenticated users can connect, mitigating ransomware risks
- Cloud-Based Authentication: Eliminates the need for RDS gateways, SSL certificates, or third-party MFA solutions
- Optimized Performance: Built-in fiber-optic mesh technology reduces latency
- Simple Deployment & Multi-Tenant Management: Implements in less than an hour and includes a multi-tenant dashboard
- Integrated MFA & Azure AD Support: Includes built-in MFA and integrates with Azure MFA & AD
- Cross-Platform Support: Works on Windows, Mac, iOS, Android, and Chrome
- 24x7 Support & Free Setup: Includes 24x7 support and free setup assistance
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NVIDIA Confidential Computing
NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
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Company Information
Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/solutions/confidential-compute
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