Google Cloud taps AMD to bring confidential computing to VMs
Google Cloud a collaboration with AMD that will see it release Confidential Computing for its latest EN2D and C2D Virtual Machines (VMs).
The first product in Google Cloud’s Confidential Computing portfolio is Confidential VM, a type of compute engine VM which Google says helps ensure that your data and applications stay private and encrypted while in use.
The latest virtual machines are powered by 3rd Gen AMD EPYC processors, and Google Cloud says it worked closely with the AMD Cloud Solution engineering team to ensure that the VM’s memory encryption doesn’t interfere with workload performance.
What is this useful for?
Google recommends N2D VMs for both general-purpose workloads and workloads that require larger virtual machine sizes and memory ratios.
This includes general-purpose workloads that require a balance of compute and memory, like web applications and databases.
Confidential N2D and C2D VMs with 3rd Gen AMD EPYC processors are set to cost the same price as the previous generation of Confidential N2D VMs
In addition, the cloud hosting giant was also able to announce that Confidential Computing is being rolled out in us-central1 (Iowa), asia-southeast1 (Singapore), us-east1 (South Carolina), us-east4 (North Virginia), asia-east1 (Taiwan), and europe-west4 (Netherlands).
How to get started?
If you already use Confidential N2D machines or are just getting started, you can use the latest hardware by simply selecting “AMD Milan or later” as the CPU platform.
To create a Confidential C2D VM, choose the C2D option when creating a new VM and check the box under “Confidential VM service” in the Google Cloud Console.
“We believe the future of computing will increasingly shift to private, encrypted services where users can be confident that their data is not being exposed to cloud providers or their own insiders,” said Joanna Young, Product Manager at Confidential Computing.
“Confidential Computing helps make this future possible by keeping data encrypted in memory, and elsewhere outside the CPU, while it is being processed – all without needing any code changes to applications.”
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