Introduction to Google Distributed Cloud
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 you have a basic understanding of Kubernetes.
Prepare for Google Distributed Cloud
Before creating a cluster in Google Distributed Cloud, you must do the following:
Create a Google Cloud project
For this quickstart, create a new Google Cloud project that organizes all your Google Cloud resources. To create a cluster in Google Distributed Cloud, you need a Google Cloud project in which your account has the Owner role.
See Create and manage projects for details.
Configure a Linux admin workstation
This quickstart uses bmctl
and kubectl
to create and work with a cluster.
This command-line tools are run on a Linux admin workstation. For information
about setting up your admin workstation, see
Admin workstation prerequisites.
Create your cluster nodes
Create two machines to serve as nodes for your cluster:
- One machine functions as the control plane node.
- One machine functions as the worker node.
Go to Cluster node machine prerequisites to learn more about the requirements for the cluster nodes.
Create 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.
Create 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. PROJECT_ID is the project you created in Create a Google Cloud project.
The command above creates a config file under the baremetal
directory at the following path: bmctl-workspace/cluster1/cluster1.yaml
Edit the config file
To edit the config file:
- Open the
bmctl-workspace/cluster1/cluster1.yaml
config file in an editor. - Edit the file with your specific node and network requirements. Use the sample config file below for reference. This quickstart doesn't use or include information on 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
---
# Cluster configuration. Note that some of these fields are immutable once the cluster is created.
# For more info, see https://cloud.google.com/anthos/clusters/docs/bare-metal/1.14/reference/cluster-config-ref#cluster_configuration_fields
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: 1.14.11
# 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 virtual IPs 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:
- 10.96.0.0/20
# 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 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: 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
# NodeConfig specifies the configuration that applies to all nodes in the cluster.
nodeConfig:
# podDensity specifies the pod density configuration.
podDensity:
# maxPodsPerNode specifies the maximum number of pods allowed on a single node.
maxPodsPerNode: 250
---
# 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_1_IP
- address: WORKER_NODE_2_IP
Run preflight checks and create the cluster
The bmctl
command runs preflight checks
on your cluster config file before it creates a cluster. If the checks are successful,
bmctl
creates the cluster.
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,
displays output to the screen, and writes verbose information
to the bmctl
logs.
You can find the bmctl
, preflight checks, and node installation
logs in the following 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.
- On Ubuntu, Uncomplicated Firewall (UFW) 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 Layer 2 subnet.
Cluster creation can take several minutes to finish.
Get information about your cluster
After you successfully create a cluster, use the kubectl
command
to show information about the new cluster. During cluster creation, the
bmctl
command writes a kubeconfig file for the cluster that you can
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 /log
directory 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
Ignore pre-flight check errors
If your cluster creation fails after pre-flight checks, you can try to re-install the
cluster 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
Create 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
.
Create the Deployment with the following command:
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 available and ready Pods:
NAME READY UP-TO-DATE AVAILABLE AGE
my-deployment 3/3 3 3 16s
The following manifest defines 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
.
Create the Service with the following command:
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
Google Distributed Cloud gives 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
Create a high availability control plane
The quickstart created 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 to add two 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>
Run the load balancer in its own node pool
The quickstart created a simple two-node hybrid cluster. Thus, 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>