Source URL: https://cloud.google.com/blog/products/identity-security/privacy-preserving-confidential-computing-now-on-even-more-machines/
Source: Cloud Blog
Title: Privacy-preserving Confidential Computing now on even more machines and services
Feedly Summary: Organizations are increasingly using Confidential Computing to help protect their sensitive data in use as part of their data protection efforts. Today, we are excited to highlight new Confidential Computing capabilities that make it easier for organizations of all sizes to adopt this important privacy-preserving technology.
1. Confidential GKE Nodes on the general-purpose C3D machine series for GKE Standard mode, generally available
Confidential GKE Nodes enforce data encryption in-use in your Google Kubernetes Engine (GKE) nodes and workloads. Confidential GKE Nodes are built on top of Compute Engine Confidential VMs using AMD Secure Encryption Virtualization (AMD SEV), which encrypts the memory contents of VMs in-use.
Previously, Confidential GKE Nodes were only available on two machine series powered by the 2nd and 3rd Gen AMD EPYC™ processors: the general-purpose N2D machine series and the compute-optimized C2D machine series. Today, Confidential GKE Nodes are also generally available on the newer, more performant C3D machine series with AMD SEV in GKE Standard mode.
The general-purpose C3D machine series is powered by 4th Gen AMD EPYC™ (Genoa) processors to deliver optimal, reliable, and consistent performance. Customers often use Confidential GKE Nodes to address potential concerns about cloud provider risk, especially since no code changes are required to enable it.
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2. Confidential GKE Nodes on GKE Autopilot mode, generally available
Google Kubernetes Engine (GKE) offers two modes of operation: Standard and Autopilot. In Standard mode, you manage the underlying infrastructure, including configuring the individual nodes. In Autopilot mode, GKE manages the underlying infrastructure such as node configuration, autoscaling, auto-upgrades, baseline security configurations, and baseline networking configuration.
Previously, Confidential GKE Nodes were only offered on GKE Standard mode. Today, Confidential GKE Nodes are generally available on GKE Autopilot mode with the general purpose N2D machine series running with AMD Secure Encryption Virtualization (AMD SEV). This means that you can now use Confidential GKE Nodes to protect your data in use without having to manage the underlying infrastructure.
Confidential GKE Nodes can be enabled on new GKE Autopilot clusters with no code changes. Simply add the command –enable-confidential-nodes during new cluster creation. Additional pricing does apply and this new offering is available in all regions that offer the N2D machine series. Go here to get started today.
3. Confidential Space with Intel TDX-based Confidential VMs, in preview
Confidential Space allows multiple parties to securely collaborate on computations using their combined data without revealing their individual datasets to each other or to the operator enabling this collaboration. This is achieved by isolating data within a Trusted Execution Environment (TEE).
We are seeing adoption and need for these capabilities that are putting sensitive data to use in a private and compliant manner in financial services, Web3, and other industries.
Confidential Space is built on Confidential VMs. Previously, Confidential Space was only available on Confidential VMs with AMD Secure Encryption Virtualization (AMD SEV) enabled. Today, Confidential Space is also available on Confidential VMs with Intel Trust Domain Extensions (Intel TDX) enabled in preview.
Confidential Space with Intel TDX enabled offers data confidentiality, data integrity, and hardware-rooted attestation, further enhancing security. Confidential Space with Intel TDX runs on the general purpose C3 machine series, which are powered by 4th Gen Intel Xeon Scalable CPUs.
These performant C3 VMs also have Intel Advanced Matrix Extensions (Intel AMX), a new built-in accelerator that helps improve the performance of deep-learning training and inference on the CPU, on by default. Confidential Space supporting the additional confidential computing type provides users greater flexibility in selecting the right CPU platform based on performance, cost, and security requirements. Learn more about Confidential Space or check out this new Youtube video about Intel TDX.
4. Confidential VMs with NVIDIA H100 GPUs, in preview
We expanded our capabilities for secure computation last year when we unveiled Confidential VMs on the accelerator-optimized A3 machine series with NVIDIA H100 GPUs. This offering extends hardware-based data protection from the CPU to GPUs, helping to ensure the confidentiality and integrity of artificial intelligence (AI), machine learning (ML), and scientific simulation workloads leveraging GPUs can be protected while data is in use.
Today, these confidential GPUs are available in preview. Confidential VMs on the A3 machine series protects data and code in use, so that means sensitive training data or data labels, proprietary models or model weights, and top secret queries remain protected even during compute-intensive operations, like training, fine tuning, or serving.
This groundbreaking technology combines the power of Confidential Computing and accelerated computing to enable customers to harness the potential of AI while helping to maintain high levels of data security and IP protection, which can open new possibilities for innovation in regulated industries and collaborative AI development.
You can sign up here to try Confidential VMs with NVIDIA H100 GPUs. To learn more, check out our previous announcements on this offering here and here.
What’s coming in 2025
Google Cloud is committed to expanding Confidential Computing to more products and services because we want customers to have easy access to the latest in security innovation. Whether that’s adding Confidential Computing support to newer hardware or on accelerators or to services like GKE Autopilot, we aim to provide our customers with a comprehensive set of Confidential Computing solutions.
Confidential Computing is an essential technology for protecting sensitive data in the cloud, and we look forward to innovating with you in this space. You can explore the Confidential Computing products here.
AI Summary and Description: Yes
Summary: The text discusses the advancements in Confidential Computing capabilities offered by Google Cloud, which enable organizations to enhance the security of sensitive data in use. Particularly noteworthy are the new Confidential GKE Nodes and Confidential Space features that leverage advanced virtualization technologies to protect data while maintaining compliance.
Detailed Description:
The provided content outlines several key developments in Google Cloud’s Confidential Computing offerings. This technology is crucial for organizations that seek to ensure the privacy and integrity of sensitive data during computation. The major points include:
– **Confidential GKE Nodes**: These nodes enforce data encryption in use on Google Kubernetes Engine (GKE), derived from AMD Secure Encryption Virtualization (SEV). Their availability has expanded from specific machine series (N2D and C2D) to the more powerful C3D machine series, providing increased performance and security.
– **GKE Operating Modes**: GKE operates in both Standard and Autopilot modes. The introduction of Confidential GKE Nodes in Autopilot mode allows for easier adoption of encryption technologies without the need for deep infrastructure management, making it more accessible for companies of varying sizes.
– **Confidential Space**: This feature enables secure collaboration between multiple parties over sensitive data without compromising individual datasets, using Intel TDX and AMD SEV for hardware-rooted security. This expands its use cases, especially in finance, Web3, and other industries that demand stringent data privacy measures.
– **Confidential VMs with NVIDIA H100 GPUs**: These virtual machines extend data protection capabilities to GPU workloads, crucial for AI, machine learning, and scientific simulations. This development emphasizes the intersection of accelerated computing and confidentiality, thus fostering innovation in industries with strict compliance needs.
– **Future Developments**: Google Cloud’s commitment to broaden Confidential Computing across its services indicates a forward-looking approach, aiming to enhance security offerings and consolidate its position as a leader in cloud security innovation.
Key Insights for Professionals:
– The expansion of Confidential Computing, particularly with offerings tailored for AI and machine learning workloads, underscores the growing need for heightened data security in cloud environments.
– Organizations leveraging these new features can enhance their compliance posture while mitigating risks associated with sensitive data exposure.
– The integration of Confidential Computing technologies can potentially enable safer collaborations across regulated industries, opening up avenues for innovation while maintaining strict confidentiality standards.
Overall, these advancements in Confidential Computing reflect a significant movement towards progressive data security solutions in cloud computing, aligned with evolving regulatory frameworks and industry demands.