WHITE PAPER

Supermicro SuperBlade with AMD EPYCTM processors powers Google Distributed Cloud Virtual deployments on-premises

Executive Summary
Table of Contents
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Drivers of On-Premises Cloud . . . . . . . . . . . . . . . . . . . . . . . . 2
Supermicro SuperBlade Product Overview . . . . . . . . . . . . 4
Solution Deployment Overview . . . . . . . . . . . . . . . . . . . . . . 5
Worker Node Machine Prerequisites . . . . . . . . . . . . . . . . . . 7
Admin Workstation Prerequisites . . . . . . . . . . . . . . . . . . . . . 9
Network Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Cluster Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Login to Google Kubernetes Engine Cluster……………. 18
Workload Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Solutione Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Key Takeaways and Business Values . . . . . . . . . . . . . . . . . 27........................ 7
and Additional©Summary2024 CopyrightSuper MicroInformation
Computer, Inc.
All rights reserved

The transformative impact of the cloud on businesses has
prompted a rapid migration and adoption of cloud-firststrategies. As a result, many enterprises are looking into
application modernization strategies to meet customer
expectations, keep business operations agile, and accelerateinnovation. Cloud-native application development empowers
enterprises to capitalize on the full power of the cloud by
delivering faster time to market, improved efficiency, increased
scalability, and better consumer experiences while optimizing
cost compared to legacy, on-premise development
infrastructures. A cloud-native approach accelerates theapplication development lifecycle by consuming independent
components called microservices, which break large monolithic
applications into smaller components.
Cloud-native technologies empower organizations to build andrun scalable applications in modern, dynamic public, private,and hybrid cloud environments. Modern cloud-native

April 20241

applications evolve rapidly; leveraging a hybrid cloud platform helps integrate variants of applications across different cloud
platforms and/or on-prem environments.
Google Distributed Cloud Virtual (GDC Virtual) is a hybrid cloud management platform that manages containers across multiple
cloud platforms and legacy VM workloads.
Businesses can leverage the benefits of GDC Virtual by deploying it on a self-managed Supermicro® SuperBlade® environment
to directly run cloud-native applications with CPU, GPU, and other hardware resources.

Drivers of On-Premises Cloud
The cloud has recently become popular for deploying new and existing applications. The simplicity and ease of using a service
can offer significant time and cost optimization compared to building your own infrastructure. Many organizations are now
adopting cloud-first strategies to leverage these advantages.
Cloud-native approaches are also increasing in popularity and encompass a broadening array of use cases from refactoring
existing applications and/or creating container-based microservices architectures. The cloud can even run legacy applications
while offering cost savings compared to on-prem deployment models.
Expanding cloud use cases empowers cloud-first organizations to run most of their application landscapes in the cloud, withfewer non-migratable exceptions. However, there is no one simple "lift-and-shift strategy" that meets the needs of every app.
Thus, no large organization currently relies solely on modern, cloud-based applications; they must work the cloud into andaround existing systems and applications, some of which do not support immediate migration to the cloud. These
applications are often the mission-critical systems at the heart of an organization's commercial operations.
The key drivers behind deciding to deploy an on-premises cloud may include:•

Data security, compliance, and data sovereignty requirements: Data sovereignty, security, and/or similar
restrictions in place because of laws, security policies, or compliance rules may prohibit an application from runningin the public cloud. This prescription often extends to Personally Identifiable Information (PII), medical, and/or othersensitive data.

•

Monolithic application design: Some legacy application architectures don't align with cloud computing pricing
models and the resulting costs and timelines of refactoring prevent organizations from migrating to the cloud.

•

Demand for very low networking latency: Highly transactional. Low-latency application systems (e.g., banking ortransportation) take an unacceptable performance hit if they are too far away from their users, data, or the next-hop
data processor in the application flow.

•

Protecting legacy infrastructure investments: Enterprises often look to optimize costs by leveraging their
existing data center investments in servers, networking equipment, and storage devices. Migrating from CapEx to
OpEx is simply not viable when the application is economically best served on existing on-premises infrastructure.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 20242

A recent IDC survey1 reveals that half of the spending on server and storage infrastructure supports on-prem deployments. As
shown in Figure 1, 71% of respondents expected to partially or fully move their workloads from a public cloud to a dedicatedIT environment in the next two years. IDC expects these investments to continue to grow at a compound annual growth rate of
2.9% for the next five years and reach $77.5 billion in 2026. Organizations keep investing in on-premises IT infrastructure
because of control, cost, and predictability.

Figure 1 – Workload Repatriation Activity.
One application modernization strategy leverages on-premises cloud solutions such as GDC Virtual to extend cloudcapabilities and services to an on-premises data center. This allows the application to leverage many of the advantages ofcloud computing while maintaining consistent operations across locations.
GDC Virtual is especially interesting to organizations already using Google Cloud Platform while seeking a seamless solution
for integrating their remaining on-premises applications into their cloud operations framework. GDC Virtual empowers
organizations to derive the benefits of cloud-based architectures while significantly reducing the costs associated with a DIY
approach across operations, lifecycle management, monitoring, and visibility—all traditionally difficult aspects of IT
operations.
GDC Virtual can deploy both traditional and cloud-native applications. Figure 2 shows a single GDC Virtual cluster supporting
deployments across multiple cloud platforms, such as Amazon AWS, Google Cloud, and Microsoft Azure. GDC Virtual also
includes a bare metal deployment option that delivers many cloud benefits to self-managed Supermicro SuperBlade servers.
1

https://www.supermicro.com/white_paper/IDC_On-Prem_Cloud_Success_Stories.pdf© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 20243

Figure 2 – Sample Google GDC Virtual Deployment.

Supermicro SuperBlade Product Overview
Supermicro SuperBlade servers deliver advanced Bare-Metal-as-a-Service (BMaaS) solutions for the global multi-cloud(hybrid, private), AI inference, visual computing, Data Center, Enterprise, Big Data, and HPC markets. SuperBlade is an ideal
platform to deploy Google Distributed Cloud Virtual for bare metal deployments. The following sections below form a solution
stack that allows you to deploy a cloud-managed platform using Supermicro SuperBlade servers powered by Google
Distributed Cloud Virtual. IT administrators can follow the procedure outlined in this section to deploy Google Distributed
Cloud Virtual on bare metal in their on-prem environments.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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SUPERMICRO AMD SUPERBLADE

SUPERMICRO AMD SUPERBLADE
8U SuperBlade Enclosure
MODELS
Supermicro's high performance, density
optimized, and energy-efficientSuperBlade® can significantly reduce initial
capital and operational expenses.

SBA-4114S-C2N/T2N
OCP 3.0 Mezzanine Cards

The Supermicro SuperBlade is powered by AMD EPYC™ Processors
Supermicro's new-generation blade portfolio helps optimize the TCO of key data
center components, such as cooling, power efficiency, node density, andnetworking management. Supermicro SuperBlade, powered by 3rd Gen AMD EPYC
processors, is built for the most demanding workloads that require high CPU
density and the fastest networking available today in a trusted platform thatmeets enterprise customer demands for on-prem private/hybrid cloud
deployments.
The Supermicro SuperBlade comes in an 8U enclosure that accommodates up to
20 hot-pluggable single socket nodes and delivers high performance with AMD
EPYC 7003 Series Processors with AMD 3D V-Cache™ technology, DDR4 3200MHz
memory, and fast PCIe® Gen4 I/O. Supermicro offers three SuperBlade models
powered by AMD EPYC processors: a SAS model, a SATA model, and a GPUaccelerated model, all of which can be mixed in a single 8U enclosure. The 8U
SuperBlade can support up to 40 single-width GPUs or 20 double-width GPUs.
SuperBlade SAS/SATA models support AIOM for front I/O, which extends the Open
Compute Project 3.0 specification to support a wide range of networking options
in a small form factor. The 8U SuperBlade also provides customers with advanced
networking options, such as 200G HDR InfiniBand and 25G Ethernet switches.
Each SuperBlade enclosure contains at least one Chassis Management Module(CMM), which allows administrators to remotely manage and monitor server
blades, power supplies, cooling fans, and networking switches. SuperCloud
Composer (SCC) is a composable cloud management platform that provides aunified dashboard for administering software-defined data centers. SCC canorchestrate cloud workloads via the streamlined industry-standard Redfish API.
SCC can also monitor and manage a broad portfolio of multi-generation
Supermicro servers from a single pane of glass, including SuperBlade.
The AMD EPYC 7003 Series Processors with AMD 3D V-Cache technology shown
below are built around the "Zen3" core and contain up to 64 cores per socket,
delivering breakthrough per-core performance with 3X the L3 Cache (768 MBs per
socket) of general purpose AMD EPYC 7003 CPUs. The Supermicro SuperBlade,
powered with AMD EPYC 7003 processors, enables exceptional HPC performance
thanks to high frequencies, core counts, high memory bandwidth and capacity,and 768MB of L3 cache.

SBA-4119SG
GPU /PCIe Cards© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 2024

5

Supermicro GPU SuperBlade SBA-4119SG supports 3rd Gen AMD 7003 Series EPYC with 3D V-Cache technology processors andthe AMD Instinct™ MI210 accelerators. These GPU-accelerated SuperBlade servers are ideal for running AI inference, visualcomputing, and HPC workloads. SuperBlade systems help organizations reduce time-to-solution for a wide range ofapplications, add advanced security features, and allow all workloads to run either on-prem or in a public or private cloud.
Supermicro SuperBlade offers high density, excellent performance, high power efficiency, and low Total Cost of Ownership(TCO).

Solution Deployment Overview
GDC Virtual on bare metal brings Google Kubernetes Engine (GKE) to your on-premises data centers and allows you to build
cloud-native workloads and manage legacy VMs. You can also leverage GDC Virtual to create, manage, and upgrade Kubernetes
clusters in your data center. The deployment described in this white paper uses GDC Virtual 1.13.1 on bare metal.
GDC Virtual on bare metal supports various cluster types:•

Admin Cluster: For cluster administration only.

•

User Cluster: For running workloads only.

•

Hybrid Cluster: For administration and running workloads, and can also manage other user clusters.

•

Standalone Cluster: For administration and running workloads, but cannot manage other user clusters.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 2024

6

Figure 3 – Google GDC Virtual Cluster Architecture deployment on Supermicro SuperBlade.

Figure 3 shows a typical GDC Virtual hybrid cluster architecture deployment on a Supermicro SuperBlade platform where
customers can choose SAS, SATA, and GPU accelerated SuperBlade nodes in an 8U enclosure. SuperBlade offers a "private
cloud in a box feature" where you can mix and match CPU-only and GPU accelerated nodes in the same 8U enclosure.
Customers can use SuperBlade to deploy the admin workstation that hosts command-line interface (CLI) tools andconfiguration files to provision clusters during installation and CLI tools for interacting with provisioned clusters postinstallation. SuperBlade can also host the Control Plane node, including the Kubernetes API server, etcd storage, and othercontrollers. You can host the worker nodes that run the actual cloud native applications on CPU- and/or GPU-powered
SuperBlade as needed for your workload(s).

The installation prerequisites are:•Supermicro SuperBlade: The deployment described in this white paper requires five (5) SuperBlade servers. Table 1
lists the minimum and recommended requirements. This example uses the SBA-4119SG as a worker node. Table 2 lists
the worker node hardware specifications.

•

GCP project: The sample project described in this whitepaper has billing enabled on the GCP Platform.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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7

•Linux Administration Workstation: A workstation used to deploy the GDC Virtual cluster. This example uses Ubuntu®
20.04.

•

Network: The Admin Workstation and cluster worker nodes must be able to access Google Cloud APIs (e.g.,*.googleapis.com).

•Worker Node Operating System – GDC Virtual supports supports CentOS (8.2, 8.3, 8.4, 8.5), RHEL (8.2, 8.3, 8.4, 8.5, 8.6),
and Ubuntu (18.04, 20.04)

Resource

Minimum

Recommended

CPUs / vCPUs

4 cores

8 cores

RAM

16GB

32GB

Storage
128GB
256GB
Table 1 - Minimum and recommended worker node hardware requirements
WORKER NODE Sample Config
Part
Type

Part #Part Description
Qty
Supermicro SuperBlade (AMD Powered Single-Socket
System
SBA-4119SG
GPU accelerated model)
1rd
3 Gen AMD EPYC 7003 Series with AMD 3D V-Cache
technology Processor (7473X - 24 Cores, 48T, 2.8GHz,
Processor PSE-MLN7473X-0507
240W TDP)
1GPU
GPU-AMDMI210-001
AMD Instinct MI210, 64GB, 300W HBM2e PCIe Gen4
1
MEM-DR464L-SL02-ER32 64GB DDR4-3200 2Rx4 LP (16Gb) ECC RDIMM
Memory8Storage
HDS-IMN0-SSDPELKX020T8 2 TB M.2 NVMe SSD
1Table 2 – A typical worker node deployed to support AI Inference workload on a GPU accelerated SuperBlade (SBA-4119SG)

Worker Node Prerequisites
The worker nodes must meet the following prerequisites:⚫

Operating System: See Select your operating system. Ubuntu 18.04 requires Linux kernel 5.4 or above.

⚫

Hardware Components: See Table 1.

⚫

Connectivity: Layer 3 to all other node machines.

⚫

NTP: Connected to NTP services.

⚫

Package Manager: apt or dnf can access the network.

⚫

API Access: *.googleapis.com.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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8

⚫

Load Balancers: Must be in the same Layer 2 subnet.

⚫

Disable ufw: GDC Virtual requires disabling ufw on Ubuntu nodes by executing the command sudo systemctl
stop ufw; sudo systemctl disable ufw on each Ubuntu node.

⚫

RHEL: Register RHEL nodes with RedHat and disable firewalld by executing the command sudo systemctl
stop firewalld; sudo systemctl disable firewalld.

⚫

Disable SELinux: Disable SELinux on RHEL nodes. Enabling SELinux may cause container creation/run
failure. In RHEL: 8, edit /etc/selinux/config file by changing SELINUX=enforcing to SELINUX=disabled, as
shown in Figure 4. Next, execute the command sudo reboot to complete the configuration. Verify that
executing getenforce shows Disable after reboot.

Figure 4 – Disabling SELinux in RHEL 8
You must configure the SSH server to grant keyless login by the Administrator Workstation to install the required packages. To
do this:⚫

Set PermitRootLogin yes in /etc/ssh/sshd_config, as shown in Figure 5.

⚫

Restart the SSH service.
sudo systemctl restart ssh⚫

Retype the password for enabling PermitRootLoginsudo passwd© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 2024

9Figure 5 – Granting root login permission

Admin Workstation Prerequisites
The Admin Workstation creates, manages, and upgrades clusters. Table 3a lists the minimum and recommended Admin
Workstation hardware requirements, and Table 3b lists the SuperBlade sample workstation configuration.

Resource

Minimum

Recommended

CPUs / vCPUs

2 cores

4 cores

RAM

Ubuntu: 4 GB CentOS/RHEL: 6 GB

Ubuntu: 8 GB CentOS/RHEL: 12 GB

Storage

128 GB
256 GB
Table 3a - Minimum and recommended Admin Workstation hardware requirements
ADMIN WORKSTATION Sample Config
Part Description

Part Type
SystemPart #
SBA-4114S-T2N

Processor
MemoryPSE-MLN7473X-0507

Supermicro SuperBlade (AMD Powered Single-Socket SATA model)
3rd Gen AMD EPYC 7003 Series with AMD 3D V-Cache technology
Processor (7473X - 24 Cores, 48T, 2.8GHz, 240W TDP)

MEM-DR464L-SL02-ER32

64GB DDR4-3200 2Rx4 LP (16Gb) ECC RDIMM

Storage

Qty
1
1
8
2
2

HDS-IMN0-SSDPELKX020T8 2 TB M.2 NVMe SSD
HDS-TUN0-KCD6XLUL1T92 1.92 TB U.2 PCIe4 NVMe SSD
Table 3b – A typical admin node deployment using AMD powered SuperBlade© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 2024

10

The Admin Workstation requires access to both Google Cloud and all cluster nodes to install and run bmctl for cluster
deployments:
A. Operating System: Verify that your operating system meets the requirements described in Select the operating
system. (https://cloud.google.com/anthos/clusters/docs/bare-metal/1.13/installing/os-reqs).
B. Docker Installation: The Administrator Workstation requires Docker for kubectl in in order to manage containers.
# sudo apt update# sudo apt install docker.io# sudo groupadd docker# sudo apt install kubectl# sudo usermod -aG docker $USER# newgrp docker // log out and log in to SSH to enable passwordless Docker
C. Google Cloud CLI Installation: Install google-cloud-cli to communicate with Google Cloud APIs for project registration.
# sudo apt-get install apt-transport-https ca-certificates gnupg# echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt
cloud-sdk main" | sudo tee -a /etc/apt/sources.list.d/google-cloud-sdk.list# curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key --keyring/usr/share/keyrings/cloud.google.gpg add # sudo apt-get update && sudo apt-get install google-cloud-cli
D. Google Cloud Configuration: Login to Google Cloud and configure your project information.
⚫

Execute gcloud auth application-default login, copy the URL to your browser to grant the permissions asshown in Figure 6, and then enter the token on the Administrator Workstation.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202411

Figure 6 – Granting permissions to Google Cloud⚫

Set the Google Cloud project quota.
#gcloud auth application-default set-quota-project your_project_id

E. Create Project: Download bmctl to create a project configuration file. The bmctl version must be consistent with the
GDC Virtual cluster. This example uses Google Anthos 1.13.1 on bare metal.
# mkdir ~/project_home# cd ~/project_home# gsutil cp gs://anthos-baremetal-release/bmctl/1.13.1/linux-amd64/bmctl .
# chmod a+x bmctl# ./bmctl create config -c your_project_id --enable-apis--create-service-accounts --project-id=your_project_id
F. Keyless SSH Setting: GDC Virtual on bare metal configures the worker node environment via keyless SSH. Set up
keyless SSH before creating the cluster. Replace the sample ID addresses below with your actual IP addresses.
# ssh-keygen -t rsa -f ~/.ssh/anthos-certification.key -C "Anthos Certification"# ssh-copy-id -i ~/.ssh/anthos-certification.key.pub root@172.17.43.169# ssh-copy-id -i ~/.ssh/anthos-certification.key.pub root@172.17.43.65# ssh-copy-id -i ~/.ssh/anthos-certification.key.pub root@172.17.43.191© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202412

# ssh-copy-id -i ~/.ssh/anthos-certification.key.pub root@172.17.43.55# ssh-copy-id -i ~/.ssh/anthos-certification.key.pub root@172.17.43.63

Network Prerequisites
GDC Virtual clusters on bare metal retrieve cluster components from the Google Cloud Container Registry and are also
registered with Google Cloud Connect Agent. If your Administrator Workstation/worker node network environment is behind aproxy server, then your proxy server must allow the specific connections shown in Table 4.

Address*.gcr.io
accounts.google.com
cloudresourcemanager.googleapis.com
compute.googleapis.com
connectgateway.googleapis.com
dl.fedoraproject.org
download.docker.com
gkeconnect.googleapis.com
gkehub.googleapis.com
gkeonprem.googleapis.com
gkeonprem.mtls.googleapis.com
iam.googleapis.com
iamcredentials.googleapis.com
logging.googleapis.com
monitoring.googleapis.com
packages.cloud.google.com
oauth2.googleapis.com
opsconfigmonitoring.googleapis.com
securetoken.googleapis.com
servicecontrol.googleapis.com
serviceusage.googleapis.com
stackdriver.googleapis.com
storage.googleapis.com
sts.googleapis.com
www.googleapis.com
Table 4 - Proxy allowed list requirements© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202413

Figure 7 shows the logical configuration of a solution stack with a non-HA control plane, which includes 1 control plane and 4
worker nodes to run user-defined workloads. Conversely, creating a hybrid cluster with a HA control plane requires at least 3
control plane nodes.

Figure 7 - Non-HA control plane
Worker nodes only require Layer 3 connectivity, but control plane load balancers require Layer 2 connectivity. Load balancer
nodes can be either the control plane nodes or a dedicated set of nodes. Load balancer nodes must meet the following
requirements:⚫

All load balance worker nodes for a given cluster must be in the same Layer 2 domain.

⚫

All virtual IP addresses are in the load balancer machine subnet and routable to the subnet's gateway.

⚫

Users are responsible for allowing the ingress of load balancer traffic.

Cluster Deployment
Verify that all prerequisites have been completed.
Edit the configuration file for deployment. This file was created by bmctl in the previous section E and saved as~/project_home/bmctl-workspace/your_project_id/your_project_id.yml. Open the file and then edit it as follows:© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 2024

14

A. Locate the SSH key path: Set the key path for keyless SSH for environment preparation.
gcrKeyPath: bmctl-workspace/.sa-keys/your_project_id-anthos-baremetal-gcr.json
sshPrivateKeyPath: /home/smci/.ssh/anthos-certification.key
gkeConnectAgentServiceAccountKeyPath: bmctl-workspace/.sa-keys/your_project_id-anthos-baremetal-connect.json
gkeConnectRegisterServiceAccountKeyPath: bmctl-workspace/.sa-keys/your_project_id-anthos-baremetal-register.json
cloudOperationsServiceAccountKeyPath: bmctl-workspace/.sa-keys/your_project_id-anthos-baremetal-cloud-ops.json

B. Meta Data Setting: Set the name of your hybrid cluster.
metadata:
name: your_project_id
namespace: cluster_your_project_id

C. Cluster Type: Cluster types include admin, user, hybrid, and standalone. This example deploys a hybrid cluster.
type: hybrid

D. Version of Google Anthos on bare metal: The cluster version must equal bmctl.
anthosBareMetalVersion: 1.13.1

E. Google Kubernetes Engine (GKE) Connect: Set the project ID for Google Kubernetes Engine (GKE).
gkeConnect:
projectID: your_project_id
F. Control Plane Node Pool: Set the IP addresses of the control plane node pool. This example only deploys one control
plane node. If you are deploying HA, then verify Layer 2 connectivity.
controlPlane:
nodePoolSpec:
nodes:# Control plane node pools. Typically, this is either a single machine.
# or 3 machines if using a high availability deployment.
- address: 172.17.43.63
G. Cluster Networking: Specify the IP ranges for Kubernetes pods and services.
clusterNetwork:# Pods specify the IP ranges from which pod networks are allocated.
pods:
cidrBlocks:- 192.168.0.0/16© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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# Services specify the network ranges from which service virtual IPs are allocated.
# This can be any RFC1918 range that does not conflict with any other IP range# in the cluster and node pool resources.
services:
cidrBlocks:- 10.96.0.0/20
H. Load Balancer: Load balancers can be 'bundled' or 'manual'. This example uses 'bundled' load balancers. The control
plane Virtual IP address(es) must not be in the address pool, but the ingress Virtual IP address must be in the address
pool.
loadBalancer:# Load balancer mode can be 'bundled' or 'manual'.
# In 'bundled' mode a load balancer will be installed on load balancer nodes during cluster creation.
# In 'manual' mode the cluster relies on a manually-configured external load balancer.
mode: bundled# Load balancer port configuration
ports:# Specifies the port the load balancer serves the Kubernetes control plane on.
# In 'manual' mode the external load balancer must be listening on this port.
controlPlaneLBPort: 443# There are two load balancer virtual IP (VIP) addresses: one for the control plane# and one for the L7 Ingress service. The VIPs must be in the same subnet as the load balancer nodes.
# These IP addresses do not correspond to physical network interfaces.
vips:# ControlPlaneVIP specifies the VIP to connect to the Kubernetes API server.
# This address must not be in the address pools below.
controlPlaneVIP: 172.17.43.221# IngressVIP specifies the VIP shared by all services for ingress traffic.
# Allowed only in non-admin clusters.
# This address must be in the address pools below.
ingressVIP: 172.17.43.222# AddressPools is a list of non-overlapping IP ranges for the data plane load balancer.
# All addresses must be in the same subnet as the load balancer nodes.
# Address pool configuration is only valid for 'bundled' LB mode in non-admin clusters.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202416

addressPools:- name: pool1
addresses:# # Each address must be either in the CIDR form (1.2.3.0/24)# # or range form (1.2.3.1-1.2.3.5).
- 172.17.43.222-172.17.43.225# A load balancer node pool can be configured to specify nodes used for load balancing.
# These nodes are part of the Kubernetes cluster and run regular workloads as well as load balancers.
# If the node pool config is absent then the control plane nodes are used.
# Node pool configuration is only valid for 'bundled' LB mode.
# nodePoolSpec:# nodes:# - address: <Machine 1 IP>
I. Cluster Operations: Configuration for logs and metrics.
clusterOperations:# Cloud project for logs and metrics.
projectID: your_project_id# Cloud location for logs and metrics.
location: us-central1# Whether collection of application logs/metrics should be enabled (in addition to# collection of system logs/metrics which correspond to system components such as# Kubernetes control plane or cluster management agents).
# enableApplication: false
J. Worker Nodes: Set the pool of worker nodes.
# Node pools for worker nodes
apiVersion: baremetal.cluster.gke.io/v1
kind: NodePool
metadata:
name: node-pool-1
namespace: cluster_your_project_id
spec:clusterName: your_project_id© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202417

nodes:- address: 172.17.43.169- address: 172.17.43.191- address: 172.17.43.55- address: 172.17.43.65
Begin deploying the GDC Virtual on the configured bare metal cluster.
A. Create Cluster: Use bmctl to create the cluster with the configuration file you edited above. This action will take several
minutes.
./bmctl create cluster -c your_project_id
B. Verify Cluster: Print the node status, as shown in Figure 8.
# kubectl --kubeconfig ~/project_home/bmctl-workspace/your_project_id/your_project_id-kubeconfig
get nodes -o wide

Figure 8 – Output of Node Status

Login to Google Kubernetes Engine Cluster
Google Kubernetes Engine manages the cluster on the Google Cloud Platform. You can use GKE to deploy workloads and use
additional applications. You can authenticate with GKE clusters via Google Identity, OIDC identity provider, or bearer tokens.
This example uses bearer tokens. Obtain the required bearer tokens by creating a Kubernetes service account (KSA) in thecluster and then using its bearer token to log in.
A. Grant roles for Google Cloud console: You must grant roles/container.viewer and roles/gkehub.viewer to interact
with connected clusters.
# gcloud projects add-iam-policy-binding your_project_id -member=user:your_persional_email@email.address --role=roles/container.viewer# gcloud projects add-iam-policy-binding your_project_id --member=user:your_persional_email@email.address --role=roles/gkehub.viewer
B. Create and apply cloud-console-reader RBAC role: Create and apply the cloud-console-reader ClusterRole to view
your cluster's resources in the Google Cloud console.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202418

# cat <<EOF > cloud-console-reader.yaml
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: cloud-console-reader
rules:- apiGroups: [""]
resources: ["nodes", "persistentvolumes", "pods"]
verbs: ["get", "list", "watch"]- apiGroups: ["storage.k8s.io"]resources: ["storageclasses"]
verbs: ["get", "list", "watch"]
EOF# kubectl apply -f cloud-console-reader.yaml --kubeconfig ~/project_home/bmctl-workspace/
your_project_id /your_project_id-kubeconfig
C. Service Account Setting: A bearer token is like a password. Create your own account and restrict operations by the
RBAC roles held by the KSA. Please replace user_account with your user account.

# kubectl create serviceaccount user_account --kubeconfig ~/project_home/bmctlworkspace/your_project_id/your_project_id-kubeconfig# kubectl create clusterrolebinding user_account --clusterrole view --serviceaccountdefault:user_account --kubeconfig ~/project_home/bmctl-workspace/your_project_id/your_project_idkubeconfig# kubectl create clusterrolebinding user_accountcloud --clusterrole cloud-console-reader -serviceaccount default:user_account --kubeconfig ~/project_home/bmctlworkspace/your_project_id/your_project_id-kubeconfig# kubectl create clusterrolebinding user_accountcluster --clusterrole cluster-admin --serviceaccountdefault:user_account --kubeconfig ~/project_home/bmctlworkspace/your_project_id/your_project_id-kubeconfig
D. Get the Bear Token: To acquire the bearer token to login to GKE:

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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# kubectl apply --kubeconfig ~/project_home/bmctl-workspace/your_project_id/your_project_idkubeconfig -f - << __EOF__
apiVersion: v1
kind: Secret
metadata:
name: "user_account-token"
annotations:kubernetes.io/service-account.name: "user_account"
type: kubernetes.io/service-account-token__EOF__# until [[ $(kubectl get --kubeconfig ~/project_home/bmctl-workspace/your_project_id/your_project_idkubeconfig -o=jsonpath="{.data.token}" "secret/user_account-token") ]]; doecho "waiting for token..." >&2;
sleep 1;done
# kubectl get secret user_account-token --kubeconfig ~/project_home/bmctlworkspace/your_project_id/your_project_id-kubeconfig -o jsonpath='{$.data.token}' | base64 –decode
E. Login via Bear Token: Click Log in, then select Token to login, as shown in Figure 9. Copy and paste the generated
token in the field, and then click LOGIN, as shown in Figure 10.

Figure 9 – Log in to GKE Cluster© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202420

Figure 10 – Paste the token and LOGIN
F. Verify the Cluster Details: You can verify the cluster details as shown in Figure 11 after a successful installation.

Figure 11 – Viewing cluster details to verify successful installation© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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Workload Examples
You can quickly deploy various workloads (AI inference, visual computing, 5G/Edge, or any other cloud-native application) in
your on-prem environment using Supermicro SuperBlade servers with GDC Virtual via the GKE console. AMD GPU accelerated
SuperBlade can be used to perform performance intensive tasks such as AI inference and large scale data processing. GKE offers
GPU-specific features, such as time-sharing and multi-instance GPUs, that can improve the efficiency with which your workloads
use the GPU resources on your nodes. Local users can visit services via exposed cluster ports. Google Container Registry also
provides different images to help rapid deployment and securely manage private images. GDC Virtual on bare metal clusters
sends regular health messages to update the health status on Google Kubernetes Engine. Google Cloud Console can display
detailed information and perform further operations, such as deploying and deleting workloads.
NGINX is a well-known, free, and open-source web server that can also function as a reverse proxy, load balancer, and HTTP
cache. Figure 12 shows a sample bare metal deployment of NGINX on SuperBlade servers powered by GDC Virtual.

Figure 12 – Sample workload deployment of GDC Virtual on SuperBlade bare metal

To deploy NGINX:© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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A.

Workload Overview: In GKE, click Workloads to see a workload overview, as shown in Figure 13.

Figure 13 – Click Workloads to see workload details

B. Deploy Workloads: Click DEPLOY to deploy workloads, as shown in Figure 14.

Figure 14 – Click DEPLOY to deploy workloads.

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C. Select Container Image for Deployment: Select an image for deployment from the Google Container Registry, andthen click CONTINUE, as shown in Figure 15.

Figure 15 – Selecting a container image for deployment© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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D. Container Configuration: Set the application name, namespace, and labels, as shown in Figure 16.

Figure 16 – Container configuration© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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E. Deployment Result: Verify successful deployment, as shown in Figure 17.

Figure 17 – Deployment Result
F. Show the Status of Container: Execute the command kubectl get pods on the Administrator Workstation to view
pod status, as shown in Figure 18.

Figure 18 – Viewing pod status on the Admin Workstation© 2024 Copyright Super Micro Computer, Inc. All rights reserved

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Solution Benefits:
Deploying GDC Virtual on Supermicro SuperBlade offers the following benefits:
•
•
•
•

•

•
•

Hardware agnostic: Customers can leverage existing on-prem SuperBlade servers to drive data center efficiency.
No hypervisor layer overhead: Deploying GDC Virtual on SuperBlade has reduced complexity.
Rapid deployment: Both developers and dev-ops teams benefit from increased productivity because GDC Virtualenables rapid cloud native application development and delivery.
Superior performance: Supermico SuperBlade, powered by AMD EPYC CPUs and/or AMD Instinct accelerators, plus
the advanced networking described above, delivers the performance needed to run today's and tomorrow's mostdemanding workloads on GDC Virtual. A large L3 Cache also reduces memory bandwidth pressure and reduces
application latency barriers.
Easy manageability: SuperBlade CMM manageability coupled with GDC Virtual management enables increased
operational efficiency (offers a dashboard with a range of health checks, logging, and monitoring).
Optimal TCO: Supermicro SuperBlade offers a building block solution with a Resource Saving Architecture that
optimizes precious data center resources, such as power, space, and cooling.
Scalability: SuperBlade enables GDC Virtual to deploy at scale across development, test, and production clusters.

Key Takeaways and Business Values
Organizations that need to keep some applications on-premises canturn to Supermicro SuperBlade servers running GDC Virtual on baremetal to transform their on-premises data center into a fully managed,
fully integrated cloud region. GDC Virtual is a cloud-native application
modernization platform that helps organizations move applications
from legacy environments to container-based microservice
architectures to reap the full benefits of cloud computing for bothcloud-native and legacy applications. GDC Virtual offers a ready-to-go,
on-premises platform that helps optimize setup and operating costs
while extending the power of Google Kubernetes Engine to SupermicroSuperBlade servers, virtualized on-prem environments, and otherpublic clouds. The Supermicro SuperBlade GDC Virtual solution is ideal
for cloud-native workload management. Supermicro SuperBladeservers can be used as control panel nodes and worker nodes to createa GDC Virtual hybrid cluster. GDC Virtual on SuperBlade delivers
consistent management, robust security features, out-of-the-box
observability, and more. Supermicro SuperBlade, powered by 3rd Gen
AMD EPYC processors, runs GDC Virtual with the operational efficiency
and consistency needed to meet various SLAs and IT initiatives andempower increased productivity, optimized TCO, and scalability in yourdata center.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 2024

BENEFITS OF DEPLOYING GDC VIRTUAL ON
SUPERMICRO SUPERBLADE
Improved productivity for development andsecurity• Faster application development, testing, anddeployment. Developers can write once anddeploy anywhere.
• Consistent, unified security policy creation andenforcement.
Streamlined Operational Efficiency• Reduced complexity with simplified management.
• Faster migrations – IT can quickly containerize,
lift and shift applications.
• Reduced effort for releases and patching.
Greener environmental impact and lower TCO• SuperBlade offers a high-density platform with
96% efficient power supplies there by reducing
the carbon footprint.
• Cost optimized building block solution for GDC
Virtual with lowest TCO.

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As a Google Distributed Cloud Virtual Ready Platform Partner, Supermicro offers a GDC Virtual Ready Platform to run GKE on
Bare Metal. We offer a robust application modernization strategy with GDC Virtual on SuperBlade. Deploying GDC Virtual on atested and validated SuperBlade yields faster time-to-market for new features and increased customer revenue by increasing
release frequencies compared to legacy approaches. GDC Virtual on bare metal SuperBlade servers helps future-proof
applications by placing them adjacent to Google's cloud services, including advanced machine learning and artificial
intelligence options. SuperBlade offers high density, high performance, optimum power efficiency, and ideal Total Cost of
Ownership (TCO) for fast, power efficient GDC Virtual deployments on bare metal.

SUPERMICROAs a global leader in high performance, high efficiency server technology and innovation, we develop and provide end-to-end green
computing solutions to the data center, cloud computing, enterprise IT, big data, HPC, and embedded markets. Our Building Block
Solutions® approach allows us to provide a broad range of SKUs, and enables us to build and deliver application-optimized solutions based
upon your requirements.

© 2024 Copyright Super Micro Computer, Inc. All rights reserved

April 202428