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Google Distributed Cloud quickstart

Introduction to Google Distributed Cloud

Google Distributed Cloud quickstart scope

With Google Distributed Cloud, you can define four types of clusters:

admin - A cluster used to manage user clusters.
user - A cluster used to run workloads.
standalone - A single cluster that can administer itself, and that can also run workloads, but can't create or manage other user clusters.
hybrid - A single cluster for both admin and workloads, that can also manage user clusters.

In this quickstart, you deploy a two-node hybrid cluster with Google Distributed Cloud. You learn how to create a cluster, and how to monitor the cluster creation process.

This quickstart assumes a basic understanding of Kubernetes

Preparing for Google Distributed Cloud

The install command of Google Distributed Cloud, called bmctl, has been designed to streamline the creation of clusters. The command can automatically set up the necessary Google service accounts and APIs you need for Google Distributed Cloud, and we'll use those automated services in this quickstart.

If you want to, you can also manually set up the necessary services and APIs before you create clusters with bmctl. We'll note the command changes you need to make later in this document, but to set up the Google services you need manually, see Enabling Google services and service accounts.

Before you can create a cluster using Google Distributed Cloud, ensure that you:

Create a Google Cloud project where you have the Editor or Owner role.
Download and install the bmctl command-line tool as described below.
Configure a Linux admin workstation for running bmctl. Note: Do not use Cloud Shell as your admin workstation.
1. Install gcloud and kubectl as described below.
2. Install Docker version 19.03 or later. (For instructions on configuring Docker, see the page for configuring your Linux OS: Configuring CentOS, Configuring RHEL, or Configuring Ubuntu.)
3. Using root access, set up SSH on both the admin workstation and the remote cluster node machines. Initially, you need root SSH password authentication enabled on the remote cluster node machines to share keys from the Admin workstation. Once the keys are in place, you can disable SSH password authentication.
4. Generate a private/public key pair on the admin workstation (do not set a passphrase for the keys). The keys are needed to use SSH for secure, passwordless connections between the administration workstation and the cluster node machines.
```
ssh-keygen -t rsa
```
  You can also use SUDO user access to the cluster node machines to set up SSH, but for passwordless, non-root user connections you need to update the cluster config YAML file with the appropriate credentials. For more information, see the #Node access configuration section in the sample cluster config file..
5. Add the generated public key to the cluster node machines. By default, the public keys are stored in the id_rsa.pub identity file.
```
ssh-copy-id -i ~/.ssh/identity_file root@cluster_node_ip
```
6. Disable SSH password authentication on the cluster node machines and use the following command on the admin workstation to verify the public key authentication works between the admin workstation and the cluster node machines.
```
ssh -o IdentitiesOnly=yes -i identity_file root@cluster_node_ip
```

Installing gcloud utilities

The gcloud and kubectl tools are included in the gcloud CLI.

On your administration machine, install and initialize the gcloud CLI using the instructions here. This process installs gcloud.
Update the gcloud CLI:
```
gcloud components update
```
Log in with your Google account so that you can manage services and service accounts:
```
gcloud auth login --update-adc
```
A new browser tab opens and you are prompted to choose an account.

Note that you can set up a Google Cloud default project at this point, and enable other services and Google APIs. before you create Google Distributed Cloud clusters. Setting a default project saves time when you enable services manually.

However, as shown in this quickstart, you can also specify a project, and set up the required Google services, directly with the bmctl command when you create your clusters. When you do this, bmctl always uses the project ID you specify when issuing the command.
Use gcloud to install kubectl:
```
gcloud components install kubectl
```

Installing bmctl

The command-line tool for creating clusters in Google Distributed Cloud is bmctl. You download bmctl from a Cloud Storage bucket

To download bmctl:

Create a new directory for bmctl:
```
cd ~
mkdir baremetal
cd baremetal
```

Download bmctl from the Cloud Storage bucket:

gcloud storage cp gs://anthos-baremetal-release/bmctl/1.6.2/linux-amd64/bmctl bmctl
chmod a+x bmctl

Ensure that bmctl is installed correctly by viewing the help information:
```
./bmctl -h
```

Creating your cluster nodes

Create two machines that will serve as nodes for your cluster:

One machine functions as the control plane node.
One machine functions as the worker node.

Note that your admin workstation needs to be able to ssh to these nodes and have access to the control plane VIP.

See hardware and operating system requirements (Centos, RHEL, and Ubuntu) for more information on what's required for the cluster nodes.

Creating a cluster

To create a cluster:

Use bmctl to create a config file.
Edit the config file to customize it for your cluster and network.
Use bmctl to create the cluster from the config file.

Creating a config file

To create a config file, and enable service accounts and APIs automatically, make sure you are in the baremetal directory, and issue the bmctl command with the following flags:

./bmctl create config -c CLUSTER_NAME \
  --enable-apis --create-service-accounts --project-id=PROJECT_ID

CLUSTER_NAME is the name of your cluster, and PROJECT_ID is a Google project where you have an Owner or Editor role.

This command creates a config file under the baremetal directory at: bmctl-workspace/cluster1/cluster1.yaml

Editing the config file

To edit the config file:

Open the bmctl-workspace/cluster1/cluster1.yaml config file in an editor.
Edit the file for your specific node and network requirements. See the sample config file below. Note that in this quickstart, we've omitted the OpenID Connect (OIDC)

# gcrKeyPath:  < to GCR service account key>
gcrKeyPath: baremetal/gcr.json
# sshPrivateKeyPath:  < to SSH private key, used for node access>
sshPrivateKeyPath: .ssh/id_rsa
# gkeConnectAgentServiceAccountKeyPath:  < to Connect agent service account key>
gkeConnectAgentServiceAccountKeyPath: baremetal/connect-agent.json
# gkeConnectRegisterServiceAccountKeyPath:  < to Hub registration service account key>
gkeConnectRegisterServiceAccountKeyPath: baremetal/connect-register.json
# cloudOperationsServiceAccountKeyPath:  < to Cloud Operations service account key>
cloudOperationsServiceAccountKeyPath: baremetal/cloud-ops.json
---
apiVersion: v1
kind: Namespace
metadata:
  name: cluster-cluster1
---
apiVersion: baremetal.cluster.gke.io/v1
kind: Cluster
metadata:
  name: cluster1
  namespace: cluster-cluster1
spec:
  # Cluster type. This can be:
  #   1) admin:  to create an admin cluster. This can later be used to create user clusters.
  #   2) user:   to create a user cluster. Requires an existing admin cluster.
  #   3) hybrid: to create a hybrid cluster that runs admin cluster components and user workloads.
  #   4) standalone: to create a cluster that manages itself, runs user workloads, but does not manage other clusters.
  type: hybrid
  # Anthos cluster version.
  anthosBareMetalVersion: 1.6.2
  # GKE connect configuration
  gkeConnect:
    projectID: PROJECT_ID
  # Control plane configuration
  controlPlane:
    nodePoolSpec:
      nodes:
      # Control plane node pools. Typically, this is either a single machine
      # or 3 machines if using a high availability deployment.
      - address:  CONTROL_PLANE_NODE_IP
  # Cluster networking configuration
  clusterNetwork:
    # Pods specify the IP ranges from which Pod networks are allocated.
    pods:
      cidrBlocks:
      - 192.168.0.0/16
    # Services specify the network ranges from which service VIPs are allocated.
    # This can be any RFC 1918 range that does not conflict with any other IP range
    # in the cluster and node pool resources.
    services:
      cidrBlocks:
      - 172.26.232.0/24
  # Load balancer configuration
  loadBalancer:
    # Load balancer mode can be either '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 LB 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 VIPs: 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.
    vips:
      # ControlPlaneVIP specifies the VIP to connect to the Kubernetes API server.
      # This address must not be in the address pools below.
      controlPlaneVIP: CONTROL_PLANE_VIP
      # 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: INGRESS_VIP
    # 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.
    # 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).
    #   - LOAD_BALANCER_ADDRESS_POOL-
    # A load balancer nodepool 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: LOAD_BALANCER_NODE_IP;
  # Proxy configuration
  # proxy:
  #   url: http://[username:password@]domain
  #   # A list of IPs, hostnames or domains that should not be proxied.
  #   noProxy:
  #   - 127.0.0.1
  #   - localhost
  # Logging and Monitoring
  clusterOperations:
    # Cloud project for logs and metrics.
    projectID: 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
  # Storage configuration
  storage:
    # lvpNodeMounts specifies the config for local PersistentVolumes backed by mounted disks.
    # These disks need to be formatted and mounted by the user, which can be done before or after
    # cluster creation.
    lvpNodeMounts:
      # path specifies the host machine path where mounted disks will be discovered and a local PV
      # will be created for each mount.
      path: /mnt/localpv-disk
      # storageClassName specifies the StorageClass that PVs will be created with. The StorageClass
      # is created during cluster creation.
      storageClassName: local-disks
    # lvpShare specifies the config for local PersistentVolumes backed by subdirectories in a shared filesystem.
    # These subdirectories are automatically created during cluster creation.
    lvpShare:
      # path specifies the host machine path where subdirectories will be created on each host. A local PV
      # will be created for each subdirectory.
      path: /mnt/localpv-share
      # storageClassName specifies the StorageClass that PVs will be created with. The StorageClass
      # is created during cluster creation.
      storageClassName: local-shared
      # numPVUnderSharedPath specifies the number of subdirectories to create under path.
      numPVUnderSharedPath: 5
---
# Node pools for worker nodes
apiVersion: baremetal.cluster.gke.io/v1
kind: NodePool
metadata:
  name: node-pool-1
  namespace: cluster-cluster1
spec:
  clusterName: cluster1
  nodes:
  - address: WORKER_NODE_IP

Running preflight checks and creating the cluster

The bmctl command runs preflight checks on your cluster config file before it creates a cluster. If they're successful, the cluster is created.

To run preflight checks and create the cluster:

Ensure that you are in the baremetal directory.
Use the following command to create the cluster:

./bmctl create cluster -c CLUSTER_NAME

./bmctl create cluster -c cluster1

The bmctl command monitors the preflight checks and cluster creation, and then displays output to the screen and writes verbose information to the bmctl logs.

The bmctl logs, as well as the preflight check and node installation logs, are in the directory: baremetal/bmctl-workspace/CLUSTER_NAME/log

The bmctl preflight checks the proposed cluster installation for the following conditions:

The Linux distribution and version are supported.
SELinux is not in "enforcing" mode.
For Ubuntu, AppArmor and UFW are not active.
For CentOS/RHEL, firewalld is not active.
Google Container Registry is reachable.
The VIPs are available.
The cluster machines have connectivity to each other.
Load balancer machines are on the same L2 subnet.

It can take several minutes to finish the cluster creation.

Getting information about your cluster

After the cluster is created successfully, the kubectl command shows you information about the new cluster. During cluster creation, the bmctl command writes a kubeconfig file for the cluster that you query with kubectl. The kubeconfig file is written to bmctl-workspace/CLUSTER_NAME/CLUSTER_NAME-kubeconfig.

For example:

kubectl --kubeconfig bmctl-workspace/cluster1/cluster1-kubeconfig get nodes

This command returns:

NAME      STATUS   ROLES    AGE   VERSION
node-01   Ready    master   16h   v1.17.8-gke.16
node-02   Ready    <none>   16h   v1.17.8-gke.16

If your cluster creation fails preflight checks, then check the preflight check logs for errors, and correct them in the cluster config file. The preflight check logs are located in the /logdirectory at

~/baremetal/bmctl-workspace/CLUSTER_NAME/log

The preflight check logs for each machine in the cluster are in the CLUSTER_NAME directory, and are organized by IP address. For example:

bmctl-workspace/cluster1/log
└── preflight-20201007-034844
    ├── 172.17.0.3
    ├── 172.17.0.4
    ├── 172.17.0.5
    ├── 172.17.0.6
    ├── 172.17.0.7
    └── node-network

Ignoring pre-flight check errors

If your cluster creation fails after pre-flight checks, you can try to re-install the cluster by using the --force flag in the bmctl command.

The --force flag installs over an existing cluster, but ignores the results from any preflight check failure due to already allocated server ports.

Ensure that you are in the baremetal directory.
Use the following command with the --force flag to re-create the cluster:

./bmctl create cluster -c CLUSTER_NAME --force

./bmctl create cluster -c cluster1 --force

Creating a Deployment and a Service

Here's a manifest for a Deployment:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-deployment
spec:
  selector:
    matchLabels:
      app: metrics
      department: sales
  replicas: 3
  template:
    metadata:
      labels:
        app: metrics
        department: sales
    spec:
      containers:
      - name: hello
        image: "gcr.io/google-samples/hello-app:2.0"

Save the manifest as my-deployment.yaml, and create the Deployment:

kubectl --kubeconfig bmctl-workspace/cluster1/cluster1-kubeconfig create -f my-deployment.yaml

View the Deployment:

kubectl --kubeconfig bmctl-workspace/cluster1/cluster1-kubeconfig get deployments

The output shows that the Deployment has three running Pods:

NAME               READY   UP-TO-DATE   AVAILABLE   AGE
my-deployment      3/3     3            3           16s

Here's a manifest for a Service of type LoadBalancer:

apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  selector:
    app: metrics
    department: sales
  type: LoadBalancer
  ports:
  - port: 80
    targetPort: 8080

Save the manifest as my-service.yaml, and create the Service:

kubectl --kubeconfig bmctl-workspace/cluster1/cluster1-kubeconfig create -f my-service.yaml

View the Service:

kubectl --kubeconfig bmctl-workspace/cluster1/cluster1-kubeconfig get service my-service

Output:

NAME         TYPE           CLUSTER-IP     EXTERNAL-IP   PORT(S
my-service   LoadBalancer   172.26.232.2   172.16.1.21   80:30060/TCP

Notice that Google Distributed Cloud has given the service an external IP address. Use the external IP address to call the Service:

curl 172.16.1.21

The output is a hello world message:

Hello, world!
Version: 2.0.0
Hostname: my-deployment-75d45b64f9-6clxj

Creating a high availability control plane

This quickstart creates a simple two-node hybrid cluster. If you want to create a high availability control plane, create a cluster that has three control plane nodes.

For example, edit the config file shown above to add to additional nodes to the control plane:

controlPlane:
  nodePoolSpec:
    clusterName: cluster1
    nodes:
    # Control Plane node pools. Typically, this is either a single machine
    # or 3 machines if using a high availability deployment.
    - address: <Machine 1 IP>
    - address: <Machine 2 IP>
    - address: <Machine 3 IP>

Running the load balancer in its own node pool

This quickstart creates a simple two-node hybrid cluster. The load balancer runs on the same node that runs the control plane.

If you want the load balancer to run in its own node pool, edit the nodePoolSpec values of the loadBalancer section of your config file:

  loadBalancer:
    nodePoolSpec:
      clusterName: "cluster1"
      nodes:
      - address: <LB Machine 1 IP>
      - address: <LB Machine 2 IP>