Try Google Distributed Cloud on Compute Engine VMs

Version 1.10 (unsupported)

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• Version 1.16
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This page shows you how to try Google Distributed Cloud in High Availability (HA) mode using Virtual Machines (VMs) running on Compute Engine.

Important: This deployment is for evaluation purposes only. Don't run Google Distributed Cloud on Compute Engine VMs in production. To deploy Google Distributed Cloud in production, follow the steps in our quickstart.

You can try out Google Distributed Cloud quickly and without having to prepare any hardware. Completing the steps on this page provides you with working test environment running on Compute Engine for your Google Distributed Cloud environment.

To try Google Distributed Cloud on Compute Engine VMs, complete the following steps:

1. Create six VMs in Compute Engine
2. Create a vxlan network between all VMs with L2 connectivity
3. Install prerequisites for Google Distributed Cloud
4. Deploy an Google Distributed Cloud cluster
5. Verify your cluster

Before you begin

The deployment requires the following resources:

• Six VMs to deploy Google Distributed Cloud
• One workstation that is logged into gcloud with Owner permissions for your project.

Note: All the commands are run on a machine that is logged into gcloud with project owner or editor credentials in the project.

Create six VMs in Compute Engine

Complete these steps to create the following VMs:

• One admin VM used to deploy Google Distributed Cloud to the other machines.
• Three VMs for the three control plane nodes needed to run the Google Distributed Cloud control plane.
• Two VMs for the two worker nodes needed to run workloads on the Google Distributed Cloud cluster.

1. Create the baremetal-gcr service account:

   export PROJECT_ID=$(gcloud config get-value project)
   export ZONE=us-central1-a
   
   gcloud iam service-accounts create baremetal-gcr
   
   gcloud iam service-accounts keys create bm-gcr.json \
   --iam-account=baremetal-gcr@${PROJECT_ID}.iam.gserviceaccount.com
   

2. Give the baremetal-gcr service account additional permissions to avoid needing multiple service accounts for different APIs and services:

   gcloud services enable \
       anthos.googleapis.com \
       anthosaudit.googleapis.com \
       anthosgke.googleapis.com \
       cloudresourcemanager.googleapis.com \
       container.googleapis.com \
       gkeconnect.googleapis.com \
       gkehub.googleapis.com \
       serviceusage.googleapis.com \
       stackdriver.googleapis.com \
       monitoring.googleapis.com \
       logging.googleapis.com \
       opsconfigmonitoring.googleapis.com
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/gkehub.connect"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/gkehub.admin"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/logging.logWriter"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/monitoring.metricWriter"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/monitoring.dashboardEditor"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/stackdriver.resourceMetadata.writer"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member="serviceAccount:baremetal-gcr@$PROJECT_ID.iam.gserviceaccount.com" \
     --role="roles/opsconfigmonitoring.resourceMetadata.writer"
   

3. Create the variables and arrays needed for all the commands on this page:

   MACHINE_TYPE=n1-standard-8
   VM_PREFIX=abm
   VM_WS=$VM_PREFIX-ws
   VM_CP1=$VM_PREFIX-cp1
   VM_CP2=$VM_PREFIX-cp2
   VM_CP3=$VM_PREFIX-cp3
   VM_W1=$VM_PREFIX-w1
   VM_W2=$VM_PREFIX-w2
   declare -a VMs=("$VM_WS" "$VM_CP1" "$VM_CP2" "$VM_CP3" "$VM_W1" "$VM_W2")
   declare -a IPs=()
   

4. Use the following loop to create six VMs:

   for vm in "${VMs[@]}"
   do
       gcloud compute instances create $vm \
                 --image-family=ubuntu-2004-lts --image-project=ubuntu-os-cloud \
                 --zone=${ZONE} \
                 --boot-disk-size 200G \
                 --boot-disk-type pd-ssd \
                 --can-ip-forward \
                 --network default \
                 --tags http-server,https-server \
                 --min-cpu-platform "Intel Haswell" \
                 --scopes cloud-platform \
                 --machine-type $MACHINE_TYPE
       IP=$(gcloud compute instances describe $vm --zone ${ZONE} \
            --format='get(networkInterfaces[0].networkIP)')
       IPs+=("$IP")
   done
   

   Note: If you intend to deploy VMs using the Anthos VM Runtime, for better performance enable hardware virtualization by adding --enable-nested-virtualization to the preceding gcloud command.

5. Use the following loop to verify that SSH is ready on all VMs:

   for vm in "${VMs[@]}"
   do
       while ! gcloud compute ssh root@$vm --zone ${ZONE} --command "echo SSH to $vm succeeded"
       do
           echo "Trying to SSH into $vm failed. Sleeping for 5 seconds. zzzZZzzZZ"
           sleep  5
       done
   done
   

Create a vxlan network with L2 connectivity between VMs

Use the standard vxlan functionality of Linux to create a network that connects all the VMs with L2 connectivity.

The following command contains two loops that perform the following actions:

1. SSH into each VM
2. Update and install needed packages

3. Execute the required commands to configure the network with vxlan

   i=2 # We start from 10.200.0.2/24
   for vm in "${VMs[@]}"
   do
       gcloud compute ssh root@$vm --zone ${ZONE} << EOF
           apt-get -qq update > /dev/null
           apt-get -qq install -y jq > /dev/null
           set -x
           ip link add vxlan0 type vxlan id 42 dev ens4 dstport 0
           current_ip=\$(ip --json a show dev ens4 | jq '.[0].addr_info[0].local' -r)
           echo "VM IP address is: \$current_ip"
           for ip in ${IPs[@]}; do
               if [ "\$ip" != "\$current_ip" ]; then
                   bridge fdb append to 00:00:00:00:00:00 dst \$ip dev vxlan0
               fi
           done
           ip addr add 10.200.0.$i/24 dev vxlan0
           ip link set up dev vxlan0
   
   EOF
       i=$((i+1))
   done
   

   Note: Starting with Google Distributed Cloud 1.8.2, you aren't required to disable AppArmor. If you use previous releases, add the following commands to the list above:

       systemctl stop apparmor.service
       systemctl disable apparmor.service
   

You now have L2 connectivity within the 10.200.0.0/24 network. The VMs have the following IP addresses:

• Admin VM: 10.200.0.2
• VMs running the control plane nodes:
  • 10.200.0.3
  • 10.200.0.4
  • 10.200.0.5
• VMs running the worker nodes:
  • 10.200.0.6
  • 10.200.0.7

Install prerequisites for Google Distributed Cloud

The following tools are needed on the admin machine before installing Google Distributed Cloud:

• bmctl
• kubectl
• Docker

1. Run the following command to install the needed tools:

   gcloud compute ssh root@$VM_WS --zone ${ZONE} << EOF
   set -x
   
   export PROJECT_ID=\$(gcloud config get-value project)
   gcloud iam service-accounts keys create bm-gcr.json \
   --iam-account=baremetal-gcr@\${PROJECT_ID}.iam.gserviceaccount.com
   
   curl -LO "https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl"
   
   chmod +x kubectl
   mv kubectl /usr/local/sbin/
   mkdir baremetal && cd baremetal
   gcloud storage cp gs://anthos-baremetal-release/bmctl/1.10.8/linux-amd64/bmctl .
   chmod a+x bmctl
   mv bmctl /usr/local/sbin/
   
   cd ~
   echo "Installing docker"
   curl -fsSL https://get.docker.com -o get-docker.sh
   sh get-docker.sh
   EOF
   

2. Run the following commands to ensure that root@10.200.0.x works. The commands perform these tasks:

   1. Generate a new SSH key on the admin machine.
   2. Add the public key to all the other VMs in the deployment.

   gcloud compute ssh root@$VM_WS --zone ${ZONE} << EOF
   set -x
   ssh-keygen -t rsa -N "" -f /root/.ssh/id_rsa
   sed 's/ssh-rsa/root:ssh-rsa/' ~/.ssh/id_rsa.pub > ssh-metadata
   for vm in ${VMs[@]}
   do
       gcloud compute instances add-metadata \$vm --zone ${ZONE} --metadata-from-file ssh-keys=ssh-metadata
   done
   EOF
   

Deploy an Google Distributed Cloud cluster

The following code block contains all commands and configurations needed to complete the following tasks:

1. Create the configuration file for the needed hybrid cluster.
2. Run the preflight checks.
3. Deploy the cluster.

Note: Copy the entire code block into the console. If you copy only parts of it, the cluster creation won't succeed.

gcloud compute ssh root@$VM_WS --zone ${ZONE} << EOF
set -x
export PROJECT_ID=$(gcloud config get-value project)
export clusterid=cluster-1
bmctl create config -c \$clusterid
cat > bmctl-workspace/\$clusterid/\$clusterid.yaml << EOB
---
gcrKeyPath: /root/bm-gcr.json
sshPrivateKeyPath: /root/.ssh/id_rsa
gkeConnectAgentServiceAccountKeyPath: /root/bm-gcr.json
gkeConnectRegisterServiceAccountKeyPath: /root/bm-gcr.json
cloudOperationsServiceAccountKeyPath: /root/bm-gcr.json
---
apiVersion: v1
kind: Namespace
metadata:
  name: cluster-\$clusterid
---
apiVersion: baremetal.cluster.gke.io/v1
kind: Cluster
metadata:
  name: \$clusterid
  namespace: cluster-\$clusterid
spec:
  type: hybrid
  anthosBareMetalVersion: 1.10.8
  gkeConnect:
    projectID: \$PROJECT_ID
  controlPlane:
    nodePoolSpec:
      clusterName: \$clusterid
      nodes:
      - address: 10.200.0.3
      - address: 10.200.0.4
      - address: 10.200.0.5
  clusterNetwork:
    pods:
      cidrBlocks:
      - 192.168.0.0/16
    services:
      cidrBlocks:
      - 172.26.232.0/24
  loadBalancer:
    mode: bundled
    ports:
      controlPlaneLBPort: 443
    vips:
      controlPlaneVIP: 10.200.0.49
      ingressVIP: 10.200.0.50
    addressPools:
    - name: pool1
      addresses:
      - 10.200.0.50-10.200.0.70
  clusterOperations:
    # might need to be this location
    location: us-central1
    projectID: \$PROJECT_ID
  storage:
    lvpNodeMounts:
      path: /mnt/localpv-disk
      storageClassName: node-disk
    lvpShare:
      numPVUnderSharedPath: 5
      path: /mnt/localpv-share
      storageClassName: local-shared
  nodeConfig:
    podDensity:
      maxPodsPerNode: 250
    containerRuntime: containerd
---
apiVersion: baremetal.cluster.gke.io/v1
kind: NodePool
metadata:
  name: node-pool-1
  namespace: cluster-\$clusterid
spec:
  clusterName: \$clusterid
  nodes:
  - address: 10.200.0.6
  - address: 10.200.0.7
EOB

bmctl create cluster -c \$clusterid
EOF

Verify your cluster

You can find your cluster's kubeconfig file on the admin machine in the bmctl-workspace directory. To verify your deployment, complete the following steps.

1. SSH into the admin workstation:

   gcloud compute ssh root@$VM_WS --zone ${ZONE}
   

2. Set the KUBECONFIG environment variable with the path to the cluster's configuration file to run kubectl commands on the cluster.

   export clusterid=cluster-1
   export KUBECONFIG=$HOME/bmctl-workspace/$clusterid/$clusterid-kubeconfig
   kubectl get nodes
   

Note: Replace $clusterid with your actual cluster name. The command uses cluster-1 because that's the value set in the previous code block when you created the cluster.

Log in to your cluster from Google Cloud console

To observe your workloads on Google Distributed Cloud in the Google Cloud console, you must log in to your admin machine where the cluster's kubeconfig file is stored.

Go to Logging in to a cluster from Google Cloud console to learn more.

Clean up

1. Connect to the admin machine to reset the cluster VMs to their state prior to installation and unregister the cluster from your Google Cloud Project:

   gcloud compute ssh root@$VM_WS --zone ${ZONE} << EOF
   set -x
   export clusterid=cluster-1
   bmctl reset -c \$clusterid
   EOF
   

   Note: Replace cluster-1 with your actual cluster name. The command uses cluster-1 because that's the value set in the earlier code block when you created the cluster.

2. List all VMs that have abm in their name:

   gcloud compute instances list | grep 'abm'
   

3. Verify that you're fine with deleting all VMs that contain abm in the name.

   After you've verified, you can delete abm VMs by running the following command:

   gcloud compute instances list --format="value(name)" | grep 'abm'  | xargs gcloud \
       --quiet compute instances delete