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    Create a Google Distributed Cloud hybrid cluster on Compute Engine VMs using Terraform

    This document shows you how to set up VMs on Compute Engine with Terraform so that you can install and try Google Distributed Cloud in high availability (HA) mode. For information about how to use the Google Cloud CLI for this, see Try Google Distributed Cloud on Compute Engine VMs .

    You can try out Google Distributed Cloud quickly and without having to prepare any hardware. The provided Terraform scripts create a network of VMs on Compute Engine that can be used to run Google Distributed Cloud. In this tutorial we use the hybrid cluster deployment model.

    Complete the following steps to get a sample cluster running:

    1. Execute the Terraform script to set up a network of VMs on Compute Engine
    2. Deploy a hybrid cluster
    3. Verify your cluster

    Before you begin

    The deployment requires the following resources:

    • One workstation with access to the internet and the following tools installed: Git , Google Cloud CLI and Terraform (>= v0.15.5, < 1.2).

    • A Google Cloud project.

      Go to project select

    • A service account in the project that satisfies one of the following requirements and its key file downloaded to the workstation:

      1. The service account has Owner permissions
      2. The service account has both Editor and Project IAM Admin permissions

      Go to Service Accounts

    Set up the VM network on Compute Engine

    In this section you use the Terraform scripts from the anthos-samples repository. The scripts configure Compute Engine with the following resources:

    • Six VMs to deploy the hybrid cluster:
      • One admin VM used to deploy the hybrid cluster to the other machines.
      • Three VMs for the three control plane nodes needed to run the hybrid cluster control plane.
      • Two VMs for the two worker nodes needed to run workloads on the hybrid cluster.
    • A VxLAN overlay network between all the nodes to emulate L2 connectivity.
    • SSH access to the control-plane and worker nodes from the admin VM .

    Bare metal infrastructure on Google Cloud using Compute Engine VMs

    You can change the number of nodes in the cluster by adding new node names to the instance_count Terraform variable:

      ################################################################################### 
 # The recommended instance count for High Availability (HA) is 3 for Control plane 
 # and 2 for Worker nodes. 
 ################################################################################### 
 variable 
  
 "instance_count" 
  
 { 
  
 description 
  
 = 
  
 "Number of instances to provision per layer (Control plane and Worker nodes) of the cluster" 
  
 type 
  
 = 
  
 map 
 ( 
 any 
 ) 
  
 default 
  
 = 
  
 { 
  
 "controlplane" 
  
 : 
  
 3 
  
 "worker" 
  
 : 
  
 2 
  
 } 
 }

    1. Download the Terraform scripts for anthos-bm-gcp-terraform sample:

       git  
clone  
https://github.com/GoogleCloudPlatform/anthos-samples cd 
  
anthos-samples/anthos-bm-gcp-terraform

    2. Update the terraform.tfvars.sample file to include variables specific to your environment:

        project_id 
  
 = 
  
 " PROJECT_ID 
" 
 region 
  
 = 
  
 " GOOGLE_CLOUD_REGION 
" 
 zone 
  
 = 
  
 " GOOGLE_CLOUD_ZONE 
" 
 credentials_file 
  
 = 
  
 " PATH_TO_GOOGLE_CLOUD_SERVICE_ACCOUNT_KEY_FILE 
"

    3. Rename the terraform.tfvars.sample file to the default name used by terraform for the variables file:

       mv  
terraform.tfvars.sample  
terraform.tfvars

    4. Initialize the sample directory as a Terraform working directory. This sets up the required Terraform state management configurations, similar to git init :

       terraform  
init

    5. Create a Terraform execution plan. This step compares the state of the resources, verifies the scripts and creates an execution plan:

       terraform  
plan

    6. Apply the changes described in the Terraform script. This step executes the plan on the given provider (in this case Google Cloud) to reach the targeted state of resources:

       terraform  
apply  
 # when prompted to confirm the Terraform plan, type 'Yes' and enter

    Deploy the hybrid cluster

    After the Terraform execution completes you are ready to deploy the hybrid cluster.

    1. Use SSH to connect to the admin host:

       gcloud  
compute  
ssh  
tfadmin@cluster1-abm-ws0-001  
--project = 
 PROJECT_ID 
  
--zone = 
 GOOGLE_CLOUD_ZONE

      You can ignore any messages about updating the VM and complete this tutorial. If you plan to keep the VMs as a test environment, you might want to update the OS or upgrade to the next release as described in the Ubuntu documentation .

    2. Run the following code block to create the cluster1 hybrid cluster on the configured Compute Engine VMs:

       sudo  
./run_initialization_checks.sh && 
 \ 
sudo  
bmctl  
create  
config  
-c  
cluster1 && 
 \ 
sudo  
cp  
~/cluster1.yaml  
bmctl-workspace/cluster1 && 
 \ 
sudo  
bmctl  
create  
cluster  
-c  
cluster1

    Running the bmctl command starts setting up a new hybrid cluster. This includes doing preflight checks on the nodes, creating the admin and user clusters and also registering the cluster with Google Cloud using Connect Agent . The whole setup can take up to 15 minutes. You see the following output as the cluster is being created:

       
Created  
config:  
bmctl-workspace/cluster1/cluster1.yaml  
Creating  
bootstrap  
cluster...  
OK  
Installing  
dependency  
components...  
OK  
Waiting  
 for 
  
preflight  
check  
job  
to  
finish...  
OK  
-  
Validation  
Category:  
machines  
and  
network  
-  
 [ 
PASSED ] 
  
 10 
.200.0.3  
-  
 [ 
PASSED ] 
  
 10 
.200.0.4  
-  
 [ 
PASSED ] 
  
 10 
.200.0.5  
-  
 [ 
PASSED ] 
  
 10 
.200.0.6  
-  
 [ 
PASSED ] 
  
 10 
.200.0.7  
-  
 [ 
PASSED ] 
  
gcp  
-  
 [ 
PASSED ] 
  
node-network  
Flushing  
logs...  
OK  
Applying  
resources  
 for 
  
new  
cluster  
Waiting  
 for 
  
cluster  
to  
become  
ready  
OK  
Writing  
kubeconfig  
file  
kubeconfig  
of  
created  
cluster  
is  
at  
bmctl-workspace/cluster1/cluster1-kubeconfig,  
please  
run  
kubectl  
--kubeconfig  
bmctl-workspace/cluster1/cluster1-kubeconfig  
get  
nodes  
to  
get  
cluster  
node  
status.  
Please  
restrict  
access  
to  
this  
file  
as  
it  
contains  
authentication  
credentials  
of  
your  
cluster.  
Waiting  
 for 
  
node  
pools  
to  
become  
ready  
OK  
Moving  
admin  
cluster  
resources  
to  
the  
created  
admin  
cluster  
Flushing  
logs...  
OK  
Deleting  
bootstrap  
cluster...  
OK

    Verify and interact with the 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. If you disconnected from the admin host, use SSH to connect to the host:

        # You can copy the command from the output of the Terraform execution above 
gcloud  
compute  
ssh  
tfadmin@cluster1-abm-ws0-001  
--project = 
 PROJECT_ID 
  
--zone = 
 GOOGLE_CLOUD_ZONE

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

        export 
  
 CLUSTER_ID 
 = 
cluster1 export 
  
 KUBECONFIG 
 = 
 $HOME 
/bmctl-workspace/ $CLUSTER_ID 
/ $CLUSTER_ID 
-kubeconfig
kubectl  
get  
nodes

      You should see the nodes of the cluster printed, similar to the following output:

       NAME  
STATUS  
ROLES  
AGE  
VERSION
cluster1-abm-cp1-001  
Ready  
master  
17m  
v1.18.6-gke.6600
cluster1-abm-cp2-001  
Ready  
master  
16m  
v1.18.6-gke.6600
cluster1-abm-cp3-001  
Ready  
master  
16m  
v1.18.6-gke.6600
cluster1-abm-w1-001  
Ready  
<none>  
14m  
v1.18.6-gke.6600
cluster1-abm-w2-001  
Ready  
<none>  
14m  
v1.18.6-gke.6600

    To observe your workloads in the Google Cloud console, you must log in to the cluster.

    For instructions and more information about logging into your cluster, see Work with clusters from the Google Cloud console .

    Clean up

    You can clean up the cluster setup in two ways.

    Console

    • If you created a dedicated project for this procedure, delete the Google Cloud project from the Google Cloud console.

      Delete Project

    Terraform

    • Unregister the cluster before deleting all the resources created by Terraform.
      # Use SSH to connect to the admin host 
gcloud  
compute  
ssh  
tfadmin@cluster1-abm-ws0-001  
--project = 
 PROJECT_ID 
  
--zone = 
 GOOGLE_CLOUD_ZONE 
 # Reset the cluster 
 export 
  
 CLUSTER_ID 
 = 
cluster1 export 
  
 KUBECONFIG 
 = 
 $HOME 
/bmctl-workspace/ $CLUSTER_ID 
/ $CLUSTER_ID 
-kubeconfig
sudo  
bmctl  
reset  
--cluster  
 $CLUSTER_ID 
 # log out of the admin host 
 exit
    • Use Terraform to delete all resources.
     terraform  
destroy  
--auto-approve
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