gke-cluster-standard

GKE Standard cluster module

This module offers a way to create and manage Google Kubernetes Engine (GKE) Standard clusters. With its sensible default settings based on best practices and authors' experience as Google Cloud practitioners, the module accommodates for many common use cases out-of-the-box, without having to rely on verbose configuration.

Important

This module should be used together with the gke-nodepool module because the default node pool is deleted upon cluster creation by default.

• Example
  • GKE Standard cluster
  • Enable Dataplane V2
  • Managing GKE logs
  • Monitoring configuration
  • Disable GKE logs or metrics collection
  • Cloud DNS
  • Backup for GKE
  • Automatic creation of new secondary ranges
  • Node auto-provisioning with GPUs and TPUs
• Variables
• Outputs

Example

GKE Standard cluster

This example shows how to create a zonal GKE cluster in Standard mode.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network    = var.vpc.self_link
    subnetwork = var.subnet.self_link
    secondary_range_names = {
      pods     = "pods"
      services = "services"
    }
    master_authorized_ranges = {
      internal-vms = "10.0.0.0/8"
    }
    master_ipv4_cidr_block = "192.168.0.0/28"
  }
  max_pods_per_node = 32
  private_cluster_config = {
    enable_private_endpoint = true
    master_global_access    = false
  }
  labels = {
    environment = "dev"
  }
}
# tftest modules=1 resources=1 inventory=basic.yaml

Enable Dataplane V2

This example shows how to create a zonal GKE Cluster with Dataplane V2 enabled.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-dataplane-v2"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {} # use default names "pods" and "services"
    master_authorized_ranges = {
      internal-vms = "10.0.0.0/8"
    }
    master_ipv4_cidr_block = "192.168.0.0/28"
  }
  private_cluster_config = {
    enable_private_endpoint = true
    master_global_access    = false
  }
  enable_features = {
    dataplane_v2        = true
    fqdn_network_policy = true
    workload_identity   = true
  }
  labels = {
    environment = "dev"
  }
}
# tftest modules=1 resources=1 inventory=dataplane-v2.yaml

Managing GKE logs

This example shows you how to control which logs are sent from your GKE cluster to Cloud Logging.

When you create a new GKE cluster, Cloud Operations for GKE integration with Cloud Logging is enabled by default and System logs are collected. You can enable collection of several other types of logs. The following example enables collection of all optional logs.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {}
  }
  logging_config = {
    enable_workloads_logs          = true
    enable_api_server_logs         = true
    enable_scheduler_logs          = true
    enable_controller_manager_logs = true
  }
}
# tftest modules=1 resources=1 inventory=logging-config-enable-all.yaml

Monitoring configuration

This example shows how to configure collection of Kubernetes control plane metrics. These metrics are optional and are not collected by default.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {} # use default names "pods" and "services"
  }
  monitoring_config = {
    enable_api_server_metrics         = true
    enable_controller_manager_metrics = true
    enable_scheduler_metrics          = true
  }
}
# tftest modules=1 resources=1 inventory=monitoring-config-control-plane.yaml

The next example shows how to configure collection of kube state metrics. These metrics are optional and are not collected by default.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {} # use default names "pods" and "services"
  }
  monitoring_config = {
    enable_daemonset_metrics   = true
    enable_deployment_metrics  = true
    enable_hpa_metrics         = true
    enable_pod_metrics         = true
    enable_statefulset_metrics = true
    enable_storage_metrics     = true
    # Kube state metrics collection requires Google Cloud Managed Service for Prometheus,
    # which is enabled by default.
    # enable_managed_prometheus = true  
  }
}
# tftest modules=1 resources=1 inventory=monitoring-config-kube-state.yaml

The control plane metrics and kube state metrics collection can be configured in a single monitoring_config block.

Disable GKE logs or metrics collection

Warning

If you've disabled Cloud Logging or Cloud Monitoring, GKE customer support is offered on a best-effort basis and might require additional effort from your engineering team.

This example shows how to fully disable logs collection on a zonal GKE Standard cluster. This is not recommended.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {}
  }
  logging_config = {
    enable_system_logs = false
  }
}
# tftest modules=1 resources=1 inventory=logging-config-disable-all.yaml

The next example shows how to fully disable metrics collection on a zonal GKE Standard cluster. This is not recommended.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = "myproject"
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {}
  }
  monitoring_config = {
    enable_system_metrics     = false
    enable_managed_prometheus = false
  }
}
# tftest modules=1 resources=1 inventory=monitoring-config-disable-all.yaml

Cloud DNS

This example shows how to use Cloud DNS as a Kubernetes DNS provider for GKE Standard clusters.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = var.project_id
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {}
  }
  enable_features = {
    dns = {
      provider = "CLOUD_DNS"
      scope    = "CLUSTER_SCOPE"
      domain   = "gke.local"
    }
  }
}
# tftest modules=1 resources=1 inventory=dns.yaml

Backup for GKE

Note

Although Backup for GKE can be enabled as an add-on when configuring your GKE clusters, it is a separate service from GKE.

Backup for GKE is a service for backing up and restoring workloads in GKE clusters. It has two components:

• A Google Cloud API that serves as the control plane for the service.
• A GKE add-on (the Backup for GKE agent) that must be enabled in each cluster for which you wish to perform backup and restore operations.

This example shows how to enable Backup for GKE on a new zonal GKE Standard cluster and plan a set of backups.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = var.project_id
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network               = var.vpc.self_link
    subnetwork            = var.subnet.self_link
    secondary_range_names = {}
  }
  backup_configs = {
    enable_backup_agent = true
    backup_plans = {
      "backup-1" = {
        region   = "europe-west2"
        schedule = "0 9 * * 1"
        applications = {
          namespace-1 = ["app-1", "app-2"]
        }
      }
    }
  }
}
# tftest modules=1 resources=2 inventory=backup.yaml

Automatic creation of new secondary ranges

You can use var.vpc_config.secondary_range_blocks to let GKE create new secondary ranges for the cluster. The example below reserves an available /14 block for pods and a /20 for services.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = var.project_id
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network    = var.vpc.self_link
    subnetwork = var.subnet.self_link
    secondary_range_blocks = {
      pods     = ""
      services = "/20" # can be an empty string as well
    }
  }
}
# tftest modules=1 resources=1

Node auto-provisioning with GPUs and TPUs

You can use var.cluster_autoscaling block to configure node auto-provisioning for the GKE cluster. The example below configures limits for CPU, memory, GPUs and TPUs.

module "cluster-1" {
  source     = "./fabric/modules/gke-cluster-standard"
  project_id = var.project_id
  name       = "cluster-1"
  location   = "europe-west1-b"
  vpc_config = {
    network    = var.vpc.self_link
    subnetwork = var.subnet.self_link
    secondary_range_blocks = {
      pods     = ""
      services = "/20"
    }
  }
  cluster_autoscaling = {
    cpu_limits = {
      max = 48
    }
    mem_limits = {
      max = 182
    }
    # Can be GPUs or TPUs
    accelerator_resources = [
      {
        resource_type = "nvidia-l4"
        max           = 2
      },
      {
        resource_type = "tpu-v5-lite-podslice"
        max           = 2
      }
    ]
  }
}
# tftest modules=1 resources=1

Variables

name	description	type	required	default
location	Cluster zone or region.	string	✓
name	Cluster name.	string	✓
project_id	Cluster project id.	string	✓
vpc_config	VPC-level configuration.	object({…})	✓
backup_configs	Configuration for Backup for GKE.	object({…})		{}
cluster_autoscaling	Enable and configure limits for Node Auto-Provisioning with Cluster Autoscaler.	object({…})		null
default_nodepool	Enable default nodepool.	object({…})		{}
deletion_protection	Whether or not to allow Terraform to destroy the cluster. Unless this field is set to false in Terraform state, a terraform destroy or terraform apply that would delete the cluster will fail.	bool		true
description	Cluster description.	string		null
enable_addons	Addons enabled in the cluster (true means enabled).	object({…})		{…}
enable_features	Enable cluster-level features. Certain features allow configuration.	object({…})		{…}
issue_client_certificate	Enable issuing client certificate.	bool		false
labels	Cluster resource labels.	map(string)		{}
logging_config	Logging configuration.	object({…})		{}
maintenance_config	Maintenance window configuration.	object({…})		{…}
max_pods_per_node	Maximum number of pods per node in this cluster.	number		110
min_master_version	Minimum version of the master, defaults to the version of the most recent official release.	string		null
monitoring_config	Monitoring configuration. Google Cloud Managed Service for Prometheus is enabled by default.	object({…})		{}
node_config	Node-level configuration.	object({…})		{}
node_locations	Zones in which the cluster's nodes are located.	list(string)		[]
private_cluster_config	Private cluster configuration.	object({…})		null
release_channel	Release channel for GKE upgrades.	string		null

Outputs

name	description	sensitive
ca_certificate	Public certificate of the cluster (base64-encoded).	✓
cluster	Cluster resource.	✓
endpoint	Cluster endpoint.
id	FUlly qualified cluster id.
location	Cluster location.
master_version	Master version.
name	Cluster name.
notifications	GKE PubSub notifications topic.
self_link	Cluster self link.	✓
workload_identity_pool	Workload identity pool.