Try Google Distributed Cloud 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:

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 desired 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

  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. 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

Log in to your cluster from Google Cloud console

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 Logging in to a cluster from Google Cloud console.

Clean up

You can clean up the cluster setup in two ways.

Console

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