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Learn how to set up a GKE cluster for your Coder deployment.
This guide shows you how to set up a Google Kubernetes Engine (GKE) cluster to which Coder can deploy.
Before proceeding, make sure that the gcloud CLI is installed on your machine and configured to interact with your Google Cloud Platform account.
Alternatively, you can create your cluster using the Google Cloud Console instead of the gcloud CLI. Please refer to the sample CLI commands below for assistance selecting the correct options for your cluster.
The node type and size that you select impact how you use Coder. When choosing, be sure to account for the number of developers you expect to use Coder, as well as the resources they need to run their workspaces. See our guide on on compute resources for additional information.
If you expect to provision GPUs to your Coder workspaces, you must use a general-purpose N1 machine type in your GKE cluster and add GPUs to the nodes. We recommend doing this in a separate GPU-specific node pool.
GPUs are not supported in workspaces deployed as container-based virtual machines (CVMs) unless you're running Coder in a bare-metal Kubernetes environment.
The following two sections will show you how to spin up a Kubernetes cluster
using the gcloud
command. See
Google's docs
for more information on each parameter used.
Regardless of which option you choose, be sure to replace the following
parameters to reflect the needs of your workspace: PROJECT_ID
,
NEW_CLUSTER_NAME
, ZONE
, and REGION
. You can
choose the zone and region
that makes the most sense for your location.
Both options include the use of the
enable-network-policy
flag, which creates a Calico cluster. See Network Policies for more information.
This option uses an Ubuntu node image to enable support of Container-based Virtual Machines (CVMs), allowing system-level functionalities such as Docker in Docker.
Please note that the sample script creates a
n1-highmem-4
instance; depending on your needs, you can choose a larger size instead. See requirements for help estimating your cluster size.
gcloud beta container --project "$PROJECT_ID" \
clusters create "$NEW_CLUSTER_NAME" \
--zone "$ZONE" \
--no-enable-basic-auth \
--node-version "latest" \
--cluster-version "latest" \
--machine-type "n1-highmem-4" \
--image-type "UBUNTU" \
--disk-type "pd-standard" \
--disk-size "50" \
--metadata disable-legacy-endpoints=true \
--scopes "https://www.googleapis.com/auth/cloud-platform" \
--num-nodes "2" \
--logging=SYSTEM,WORKLOAD \
--monitoring=SYSTEM \
--enable-ip-alias \
--network "projects/$PROJECT_ID/global/networks/default" \
--subnetwork "projects/$PROJECT_ID/regions/$REGION/subnetworks/default" \
--default-max-pods-per-node "110" \
--addons HorizontalPodAutoscaling,HttpLoadBalancing \
--enable-autoupgrade \
--enable-autorepair \
--enable-network-policy \
--enable-autoscaling \
--min-nodes "1" \
--max-nodes "8"
This option uses a Container-Optimized OS (COS) and meets Coder's minimum requirements. It does not enable the use of CVMs.
Please note that the sample script creates a
n1-highmem-4
instance; depending on your needs, you can choose a larger size instead. See requirements for help estimating your cluster size.
gcloud beta container --project "$PROJECT_ID" \
clusters create "$NEW_CLUSTER_NAME" \
--zone "$ZONE" \
--no-enable-basic-auth \
--cluster-version "latest" \
--machine-type "n1-highmem-4" \
--image-type "COS" \
--disk-type "pd-standard" \
--disk-size "50" \
--metadata disable-legacy-endpoints=true \
--scopes "https://www.googleapis.com/auth/cloud-platform" \
--num-nodes "2" \
--logging=SYSTEM,WORKLOAD \
--monitoring=SYSTEM \
--enable-ip-alias \
--network "projects/$PROJECT_ID/global/networks/default" \
--subnetwork "projects/$PROJECT_ID/regions/$REGION/subnetworks/default" \
--default-max-pods-per-node "110" \
--addons HorizontalPodAutoscaling,HttpLoadBalancing \
--enable-autoupgrade \
--enable-autorepair \
--enable-network-policy \
--enable-autoscaling \
--min-nodes "1" \
--max-nodes "8"
This process may take ~15-30 minutes to complete.
GKE allows you to integrate Identity Access and Management (IAM) with Kubernetes' native Role-Based Access Control (RBAC) mechanism to authorize user actions in the cluster. IAM configuration is primarily applied at the project level and to all clusters within that project. Kubernetes RBAC configuration applies to individual clusters, allowing you to implement fine-grained authorization right down to the namespace level.
For more information, see:
If you have already installed Coder or are using our hosted beta, you can add this cluster as a workspace provider.
To access Coder through a secure domain, review our guides on configuring and using TLS certificates.
Once complete, see our page on installation.
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