Files
genai-toolbox/docs/en/how-to/deploy_gke.md
Yuan Teoh 17b41f6453 feat: add allowed-hosts flag (#2254)
## Description

Previously added `allowed-origins` (for CORs) is not sufficient for
preventing DNS rebinding attacks. We'll have to check host headers.

To test, run Toolbox with the following:
```
go run . --allowed-hosts=127.0.0.1:5000
```

Test with the following:
```
// curl successfully
curl -H "Host: 127.0.0.1:5000" http://127.0.0.1:5000

// will show Invalid Host Header error
curl -H "Host: attacker:5000" http://127.0.0.1:5000
```

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> Thank you for opening a Pull Request! Before submitting your PR, there
are a
> few things you can do to make sure it goes smoothly:

- [ ] Make sure you reviewed

[CONTRIBUTING.md](https://github.com/googleapis/genai-toolbox/blob/main/CONTRIBUTING.md)
- [ ] Make sure to open an issue as a

[bug/issue](https://github.com/googleapis/genai-toolbox/issues/new/choose)
  before writing your code! That way we can discuss the change, evaluate
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🛠️ Fixes #<issue_number_goes_here>
2026-01-08 19:42:54 +00:00

7.1 KiB

title, type, weight, description
title type weight description
Deploy to Kubernetes docs 4 How to set up and configure Toolbox to deploy on Kubernetes with Google Kubernetes Engine (GKE).

Before you begin

  1. Set the PROJECT_ID environment variable:

    export PROJECT_ID="my-project-id"
    
  2. Install the gcloud CLI.

  3. Initialize gcloud CLI:

    gcloud init
    gcloud config set project $PROJECT_ID
    
  4. You must have the following APIs enabled:

    gcloud services enable artifactregistry.googleapis.com \
                           cloudbuild.googleapis.com \
                           container.googleapis.com \
                           iam.googleapis.com
    
  5. kubectl is used to manage Kubernetes, the cluster orchestration system used by GKE. Verify if you have kubectl installed:

    kubectl version --client
    
  6. If needed, install kubectl component using the Google Cloud CLI:

    gcloud components install kubectl
    

Create a service account

  1. Specify a name for your service account with an environment variable:

    export SA_NAME=toolbox
    
  2. Create a backend service account:

    gcloud iam service-accounts create $SA_NAME
    
  3. Grant any IAM roles necessary to the IAM service account. Each source has a list of necessary IAM permissions listed on its page. The example below is for cloud sql postgres source:

    gcloud projects add-iam-policy-binding $PROJECT_ID \
        --member serviceAccount:$SA_NAME@$PROJECT_ID.iam.gserviceaccount.com \
        --role roles/cloudsql.client
    

Deploy to Kubernetes

  1. Set environment variables:

    export CLUSTER_NAME=toolbox-cluster
    export DEPLOYMENT_NAME=toolbox
    export SERVICE_NAME=toolbox-service
    export REGION=us-central1
    export NAMESPACE=toolbox-namespace
    export SECRET_NAME=toolbox-config
    export KSA_NAME=toolbox-service-account
    
  2. Create a GKE cluster.

    gcloud container clusters create-auto $CLUSTER_NAME \
        --location=us-central1
    
  3. Get authentication credentials to interact with the cluster. This also configures kubectl to use the cluster.

    gcloud container clusters get-credentials $CLUSTER_NAME \
        --region=$REGION \
        --project=$PROJECT_ID
    
  4. View the current context for kubectl.

    kubectl config current-context
    
  5. Create namespace for the deployment.

    kubectl create namespace $NAMESPACE
    
  6. Create a Kubernetes Service Account (KSA).

    kubectl create serviceaccount $KSA_NAME --namespace $NAMESPACE
    
  7. Enable the IAM binding between Google Service Account (GSA) and Kubernetes Service Account (KSA).

    gcloud iam service-accounts add-iam-policy-binding \
        --role="roles/iam.workloadIdentityUser" \
        --member="serviceAccount:$PROJECT_ID.svc.id.goog[$NAMESPACE/$KSA_NAME]" \
        $SA_NAME@$PROJECT_ID.iam.gserviceaccount.com
    
  8. Add annotation to KSA to complete binding:

    kubectl annotate serviceaccount \
        $KSA_NAME \
        iam.gke.io/gcp-service-account=$SA_NAME@$PROJECT_ID.iam.gserviceaccount.com \
        --namespace $NAMESPACE
    
  9. Prepare the Kubernetes secret for your tools.yaml file.

    kubectl create secret generic $SECRET_NAME \
        --from-file=./tools.yaml \
        --namespace=$NAMESPACE
    
  10. Create a Kubernetes manifest file (k8s_deployment.yaml) to build deployment.

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: toolbox
      namespace: toolbox-namespace
    spec:
      selector:
        matchLabels:
          app: toolbox
      template:
        metadata:
          labels:
            app: toolbox
        spec:
          serviceAccountName: toolbox-service-account
          containers:
            - name: toolbox
              # Recommend to use the latest version of toolbox
              image: us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:latest
              args: ["--address", "0.0.0.0"]
              ports:
                - containerPort: 5000
              volumeMounts:
                - name: toolbox-config
                  mountPath: "/app/tools.yaml"
                  subPath: tools.yaml
                  readOnly: true
          volumes:
            - name: toolbox-config
              secret:
                secretName: toolbox-config
                items:
                - key: tools.yaml
                  path: tools.yaml
    

    {{< notice tip >}} To prevent DNS rebinding attack, use the --allowed-origins flag to specify a list of origins permitted to access the server. E.g. args: ["--address", "0.0.0.0", "--allowed-hosts", "foo.bar:5000"]

To implement CORs, use the --allowed-origins flag to specify a list of origins permitted to access the server. E.g. args: ["--address", "0.0.0.0", "--allowed-origins", "https://foo.bar"] {{< /notice >}}

  1. Create the deployment.

    kubectl apply -f k8s_deployment.yaml --namespace $NAMESPACE
    
  2. Check the status of deployment.

    kubectl get deployments --namespace $NAMESPACE
    
  3. Create a Kubernetes manifest file (k8s_service.yaml) to build service.

    apiVersion: v1
    kind: Service
    metadata:
      name: toolbox-service
      namespace: toolbox-namespace
      annotations:
        cloud.google.com/l4-rbs: "enabled"
    spec:
      selector:
        app: toolbox
      ports:
        - port: 5000
          targetPort: 5000
      type: LoadBalancer
    
  4. Create the service.

    kubectl apply -f k8s_service.yaml --namespace $NAMESPACE
    
  5. You can find your IP address created for your service by getting the service information through the following.

    kubectl describe services $SERVICE_NAME --namespace $NAMESPACE
    
  6. To look at logs, run the following.

    kubectl logs -f deploy/$DEPLOYMENT_NAME --namespace $NAMESPACE
    
  7. You might have to wait a couple of minutes. It is ready when you can see EXTERNAL-IP with the following command:

    kubectl get svc -n $NAMESPACE
    
  8. Access toolbox locally.

    curl <EXTERNAL-IP>:5000
    

Clean up resources

  1. Delete secret.

    kubectl delete secret $SECRET_NAME --namespace $NAMESPACE
    
  2. Delete deployment.

    kubectl delete deployment $DEPLOYMENT_NAME --namespace $NAMESPACE
    
  3. Delete the application's service.

    kubectl delete service $SERVICE_NAME --namespace $NAMESPACE
    
  4. Delete the Kubernetes cluster.

    gcloud container clusters delete $CLUSTER_NAME \
        --location=$REGION