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docs: move compute benchmarks to own page
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@ -51,7 +51,7 @@ Encrypting your K8s is good for:
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* High availability with multi-master architecture and stacked etcd topology
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* Dynamic cluster autoscaling with verification and secure bootstrapping of new nodes
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* Competitive performance ([see K-Bench comparison with AKS and GKE][performance])
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* Competitive [performance]
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### 🧩 Easy to use and integrate
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11
docs/docs/overview/performance/compute.md
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docs/docs/overview/performance/compute.md
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# Impact of runtime encryption on compute performance
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All nodes in a Constellation cluster are executed inside Confidential VMs (CVMs). Consequently, the performance of Constellation is inherently linked to the performance of these CVMs.
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## AMD and Azure benchmarking
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AMD and Azure have collectively released a [performance benchmark](https://community.amd.com/t5/business/microsoft-azure-confidential-computing-powered-by-3rd-gen-epyc/ba-p/497796) for CVMs that utilize 3rd Gen AMD EPYC processors (Milan) with SEV-SNP. This benchmark, which included a variety of mostly compute-intensive tests such as SPEC CPU 2017 and CoreMark, demonstrated that CVMs experience only minor performance degradation (ranging from 2% to 8%) when compared to standard VMs. Such results are indicative of the performance that can be expected from compute-intensive workloads running with Constellation on Azure.
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## AMD and Google benchmarking
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Similarly, AMD and Google have jointly released a [performance benchmark](https://www.amd.com/system/files/documents/3rd-gen-epyc-gcp-c2d-conf-compute-perf-brief.pdf) for CVMs employing 3rd Gen AMD EPYC processors (Milan) with SEV-SNP. With high-performance computing workloads such as WRF, NAMD, Ansys CFS, and Ansys LS_DYNA, they observed analogous findings, with only minor performance degradation (between 2% and 4%) compared to standard VMs. These outcomes are reflective of the performance that can be expected for compute-intensive workloads running with Constellation on GCP.
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# Performance analysis of Constellation
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This section provides a comprehensive examination of the performance characteristics of Constellation, encompassing various aspects, including runtime encryption, I/O benchmarks, and real-world applications.
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This section provides a comprehensive examination of the performance characteristics of Constellation.
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## Impact of runtime encryption on performance
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## Runtime encryption
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All nodes in a Constellation cluster are executed inside Confidential VMs (CVMs). Consequently, the performance of Constellation is inherently linked to the performance of these CVMs.
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### AMD and Azure benchmarking
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AMD and Azure have collectively released a [performance benchmark](https://community.amd.com/t5/business/microsoft-azure-confidential-computing-powered-by-3rd-gen-epyc/ba-p/497796) for CVMs that utilize 3rd Gen AMD EPYC processors (Milan) with SEV-SNP. This benchmark, which included a variety of mostly compute-intensive tests such as SPEC CPU 2017 and CoreMark, demonstrated that CVMs experience only minor performance degradation (ranging from 2% to 8%) when compared to standard VMs. Such results are indicative of the performance that can be expected from compute-intensive workloads running with Constellation on Azure.
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### AMD and Google benchmarking
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Similarly, AMD and Google have jointly released a [performance benchmark](https://www.amd.com/system/files/documents/3rd-gen-epyc-gcp-c2d-conf-compute-perf-brief.pdf) for CVMs employing 3rd Gen AMD EPYC processors (Milan) with SEV-SNP. With high-performance computing workloads such as WRF, NAMD, Ansys CFS, and Ansys LS_DYNA, they observed analogous findings, with only minor performance degradation (between 2% and 4%) compared to standard VMs. These outcomes are reflective of the performance that can be expected for compute-intensive workloads running with Constellation on GCP.
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Runtime encryption affects compute performance. [Benchmarks by Azure and Google](compute.md) show that the performance degradation of Confidential VMs (CVMs) is small, ranging from 2% to 8% for compute-intensive workloads.
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## I/O performance benchmarks
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@ -55,6 +55,11 @@ const sidebars = {
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label: 'Performance',
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link: { type: 'doc', id: 'overview/performance/performance' },
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items: [
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{
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type: 'doc',
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label: 'Compute benchmarks',
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id: 'overview/performance/compute',
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},
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{
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type: 'doc',
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label: 'I/O benchmarks',
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