Before you begin
Overview
Your GKE cluster must meet the following requirements:
Optional, but recommended, the cluster should be dedicated to Kf. We recommend that you only install Kf and its dependencies to ensure that the compatibility matrix is maintained.
At least four nodes. If you need to add nodes, see Resizing a cluster.
The minimum machine type that has at least four vCPUs, such as
e2-standard-4
. If the machine type for your cluster doesn't have at least four vCPUs, change the machine type as described in Migrating workloads to different machine types.Optional, but recommended, enroll the cluster in a release channel. Follow the instructions in Enrolling an existing cluster in a release channel if you have a static GKE version.
Workload Identity enabled.
Artifact Registry enabled.
Tekton installed. See the Dependency matrix for the version.
A Google Service Account with the following IAM policy (creation instructions linked below):
roles/iam.serviceAccountAdmin
serviceAccount:${CLUSTER_PROJECT}.svc.id.goog[kf/controller]
(for memberserviceAccount:${CLUSTER_PROJECT}.svc.id.goog[kf/controller]
)
The Clean up section has instructions on deleting the cluster.
Enable support for Compute Engine
- Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
- Enable the Compute Engine API.
Enable and configure GKE
Before you start, make sure you have performed the following tasks:
- Enable the Google Kubernetes Engine API. Enable Google Kubernetes Engine API
- If you want to use the Google Cloud CLI for this task,
install and then
initialize the
gcloud CLI. If you previously installed the gcloud CLI, get the latest
version by running
gcloud components update
.
Create and prepare a new GKE cluster
Setup environment variables
Linux
export PROJECT_ID=YOUR_PROJECT_ID export CLUSTER_PROJECT_ID=YOUR_PROJECT_ID export CLUSTER_NAME=kf-cluster export COMPUTE_ZONE=us-central1-a export COMPUTE_REGION=us-central1 export CLUSTER_LOCATION=${COMPUTE_ZONE} export NODE_COUNT=4 export MACHINE_TYPE=e2-standard-4 export NETWORK=default export KF_VERSION=v2.1.0 export TEKTON_VERSION=v0.19.0
Windows Powershell
Set-Variable -Name PROJECT_ID -Value YOUR_PROJECT_ID Set-Variable -Name CLUSTER_PROJECT_ID -Value YOUR_PROJECT_ID Set-Variable -Name CLUSTER_NAME -Value kf-cluster Set-Variable -Name COMPUTE_ZONE -Value us-central1-a Set-Variable -Name COMPUTE_REGION -Value us-central1 Set-Variable -Name CLUSTER_LOCATION -Value $COMPUTE_ZONE Set-Variable -Name NODE_COUNT -Value 4 Set-Variable -Name MACHINE_TYPE -Value e2-standard-4 Set-Variable -Name NETWORK -Value default Set-Variable -Name KF_VERSION -Value v2.1.0 Set-Variable -Name TEKTON_VERSION -Value v0.19.0
Service account setup
Create a GCP service account (GSA) that will be associated with a Kubernetes Service Account via Workload Identity. This prevents the need to create and inject a service account key.
Create the service account that Kf will use.
gcloud iam service-accounts create ${CLUSTER_NAME}-sa \ --project=${CLUSTER_PROJECT_ID} \ --description="GSA for Kf ${CLUSTER_NAME}" \ --display-name="${CLUSTER_NAME}"
Allow the service account to modify its own policy. The Kf controller will use this to add new (name)spaces to the policy, allowing reuse for Workload Identity.
gcloud iam service-accounts add-iam-policy-binding ${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com \ --project=${CLUSTER_PROJECT_ID} \ --role="roles/iam.serviceAccountAdmin" \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com"
Give monitoring metrics role for write access to Cloud Monitoring.
gcloud projects add-iam-policy-binding ${CLUSTER_PROJECT_ID} \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --role="roles/monitoring.metricWriter"
Give logging role for write access to Cloud Logging.
gcloud projects add-iam-policy-binding ${CLUSTER_PROJECT_ID} \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --role="roles/logging.logWriter"
Create GKE cluster
gcloud container clusters create ${CLUSTER_NAME} \ --project=${CLUSTER_PROJECT_ID} \ --zone=${CLUSTER_LOCATION} \ --num-nodes=${NODE_COUNT} \ --machine-type=${MACHINE_TYPE} \ --network=${NETWORK} \ --addons=HttpLoadBalancing,HorizontalPodAutoscaling,NetworkPolicy \ --enable-stackdriver-kubernetes \ --enable-ip-alias \ --enable-network-policy \ --enable-autorepair \ --enable-autoupgrade \ --scopes=https://www.googleapis.com/auth/cloud-platform \ --release-channel=regular \ --workload-pool="${CLUSTER_PROJECT_ID}.svc.id.goog" \ --service-account="${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com"
Set firewall rules
Kf requires some firewall ports to be open. The master node needs to be able to communicate with pods on ports 80, 443, 8080, 8443 and 6443.
Enable Workload Identity
Now that you have a service account and GKE cluster, associate the cluster's identity namespace with the cluster.
gcloud iam service-accounts add-iam-policy-binding \ "${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --project=${CLUSTER_PROJECT_ID} \ --role="roles/iam.workloadIdentityUser" \ --member="serviceAccount:${CLUSTER_PROJECT_ID}.svc.id.goog[kf/controller]"
Target GKE cluster
Configure kubectl command line access by running the following command.
gcloud container clusters get-credentials ${CLUSTER_NAME} \ --project=${CLUSTER_PROJECT_ID} \ --zone=${CLUSTER_LOCATION}
Create an Artifact Registry repository
Create an Artifact Registry for container images to be stored.
gcloud artifacts repositories create ${CLUSTER_NAME} \ --repository-format=docker \ --location=${COMPUTE_REGION}
Grant the service account permission on the Artifact Registry repository.
gcloud artifacts repositories add-iam-policy-binding ${CLUSTER_NAME} \ --location=${COMPUTE_REGION} \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --role='roles/artifactregistry.writer'
Configure your local authentication.
gcloud auth configure-docker ${COMPUTE_REGION}-docker.pkg.dev
Install software dependencies on cluster
Install Tekton:
kubectl apply -f "https://github.com/tektoncd/pipeline/releases/download/${TEKTON_VERSION}/release.yaml"
Install Kf
See Create and prepare a GKE cluster for Kf to create a cluster prepared to run Kf.
Select and note the desired Kf release. Reference the Kf Downloads page for available versions
Install CLI:
Linux
This will install
kf
for all users on the system. Follow the instructions in the Cloud Shell tab to install it just for yourself.gcloud storage cp gs://kf-releases/${KF_VERSION}/kf-linux /tmp/kf
chmod a+x /tmp/kf
sudo mv /tmp/kf /usr/local/bin/kf
Mac
This will install
kf
for all users on the system.gcloud storage cp gs://kf-releases/${KF_VERSION}/kf-darwin /tmp/kf
chmod a+x /tmp/kf
sudo mv /tmp/kf /usr/local/bin/kf
Cloud Shell
This will install
kf
on your Cloud Shell instance if you usebash
, the instructions may need to be modified for other shells.mkdir -p ~/bin
gcloud storage cp gs://kf-releases/${KF_VERSION}/kf-linux ~/bin/kf
chmod a+x ~/bin/kf
echo "export PATH=$HOME/bin:$PATH" >> ~/.bashrc
source ~/.bashrc
Windows
This will download
kf
to current directory. Add it to the path if you want to call if from anywhere other than the current directory.gcloud storage cp gs://kf-releases/${KF_VERSION}/kf-windows.exe kf.exe
Install server components:
Linux and Mac
This will download kf.yaml to current directory.
gcloud storage cp gs://kf-releases/${KF_VERSION}/kf.yaml /tmp/kf.yaml
kubectl apply -f /tmp/kf.yaml
Windows
This will download kf.yaml to current directory.
gcloud storage cp gs://kf-releases/${KF_VERSION}/kf.yaml kf.yaml
kubectl apply -f kf.yaml
Setup secrets:
export WI_ANNOTATION=iam.gke.io/gcp-service-account=${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com kubectl annotate serviceaccount controller ${WI_ANNOTATION} \ --namespace kf \ --overwrite echo "{\"apiVersion\":\"v1\",\"kind\":\"ConfigMap\",\"metadata\":{\"name\":\"config-secrets\", \"namespace\":\"kf\"},\"data\":{\"wi.googleServiceAccount\":\"${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com\"}}" | kubectl apply -f -
Setup Kf defaults, these values can be changed later. The example below uses domain templates with a wildcard DNS provider to provide each Space its own domain name:
export CONTAINER_REGISTRY=${COMPUTE_REGION}-docker.pkg.dev/${CLUSTER_PROJECT_ID}/${CLUSTER_NAME} export DOMAIN='$(SPACE_NAME).$(CLUSTER_INGRESS_IP).nip.io' kubectl patch configmaps config-defaults \ -n=kf \ -p="{\"data\":{\"spaceContainerRegistry\":\"${CONTAINER_REGISTRY}\",\"spaceClusterDomains\":\"- domain: ${DOMAIN}\"}}"
Validate installation:
kf doctor --retries 10
Pushing an application
Prerequisites
The following are required to complete this section:
- Kf installed in a compatible GKE cluster. See Install Kf for instructions.
- A
.kubeconfig
targeting the Kf cluster. If you created the cluster per the instructions in this document, this will already be done. You can explicilty generate the config withgcloud container clusters get-credentials ${CLUSTER_NAME} --zone ${CLUSTER_LOCATION}
- The
kf
CLI installed and in your path. See Install Kf for instructions. - The
git
CLI installed and in your path.
Prepare space
Create new space:
kf create-space test-space
Target the space:
kf target -s test-space
Push the Cloud Foundry test app
Clone the test-app repo:
git clone https://github.com/cloudfoundry-samples/test-app go-test-app cd go-test-app
Push the app:
kf push test-app
Find the application's URL:
Use output formatting to retrieve just the route:
kf app test-app --output 'jsonpath={.status.urls[0]}'
Or this for a more traditional CF approach:
kf apps
Open the URL in your browser.
Clean up
These steps should remove all the components created in the Create and prepare a new GKE cluster section.
Delete GKE cluster:
gcloud container clusters delete ${CLUSTER_NAME} --zone ${CLUSTER_LOCATION}
Delete Google Service Account:
gcloud iam service-accounts delete ${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com
Delete IAM policy bindings:
gcloud projects remove-iam-policy-binding ${CLUSTER_PROJECT_ID} \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --role="roles/storage.admin" gcloud projects remove-iam-policy-binding ${CLUSTER_PROJECT_ID} \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --role="roles/iam.serviceAccountAdmin" gcloud projects remove-iam-policy-binding ${CLUSTER_PROJECT_ID} \ --member="serviceAccount:${CLUSTER_NAME}-sa@${CLUSTER_PROJECT_ID}.iam.gserviceaccount.com" \ --role="roles/monitoring.metricWriter"
Delete container image repository:
gcloud artifacts repositories delete ${CLUSTER_NAME} \ --location=${COMPUTE_REGION}