docs: move compute benchmarks to own page

README.md

@@ -51,7 +51,7 @@ Encrypting your K8s is good for:
 
 * High availability with multi-master architecture and stacked etcd topology
 * Dynamic cluster autoscaling with verification and secure bootstrapping of new nodes
-* Competitive performance ([see K-Bench comparison with AKS and GKE][performance])
+* Competitive [performance]
 
 ### 🧩 Easy to use and integrate
 

docs/docs/overview/performance/compute.md

@@ -0,0 +1,11 @@
+# Impact of runtime encryption on compute performance
+
+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.
+
+## AMD and Azure benchmarking
+
+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.
+
+## AMD and Google benchmarking
+
+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.

docs/docs/overview/performance/performance.md

@@ -1,18 +1,10 @@
 # Performance analysis of Constellation
 
-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.
+This section provides a comprehensive examination of the performance characteristics of Constellation.
 
-## Impact of runtime encryption on performance
+## Runtime encryption
 
-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.
+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.
-
-### AMD and Azure benchmarking
-
-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.
-
-### AMD and Google benchmarking
-
-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.
 
 ## I/O performance benchmarks
 

docs/sidebars.js

@@ -55,6 +55,11 @@ const sidebars = {
           label: 'Performance',
           link: { type: 'doc', id: 'overview/performance/performance' },
           items: [
+            {
+              type: 'doc',
+              label: 'Compute benchmarks',
+              id: 'overview/performance/compute',
+            },
             {
               type: 'doc',
               label: 'I/O benchmarks',