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Install on GCP

Self-managed Materialize requires: a Kubernetes (v1.29+) cluster; PostgreSQL as a metadata database; and blob storage.

This tutorial deploys Materialize to GCP Google Kubernetes Engine (GKE) cluster with a Cloud SQL PostgreSQL database as the metadata database and Cloud Storage bucket for blob storage. Specifically, the tutorial uses Materialize on Google Cloud Terraform modules to:

  • Set up the GCP environment.

  • Call terraform-helm-materialize module to deploy Materialize Operator and Materialize instances to the GKE cluster.

WARNING! The Terraform modules used in this tutorial are provided for demonstration/evaluation purposes only and not intended for production use. Materialize does not support nor recommend these modules for production use.

Prerequisites

Google cloud project

You need a GCP project for which you have a role (such as roles/resourcemanager.projectIamAdmin or roles/owner) that includes permissions to manage access to the project.

gcloud CLI

If you do not have gcloud CLI, install. For details, see the Install the gcloud CLI documentation.

Google service account

The tutorial assumes the use of a service account. If you do not have a service account to use for this tutorial, create a service account. For details, see Create service accounts.

Terraform

If you do not have Terraform installed, install Terraform.

kubectl and plugins

💡 Tip: Using gcloud to install kubectl will also install the needed plugins. Otherwise, you will need to manually install the gke-gcloud-auth-plugin for kubectl.

Helm 3.2.0+

If you do not have Helm version 3.2.0+ installed, install. For details, see the Helm documentation.

jq (Optional)

Optional. jq is used to parse the EKS cluster name and region from the Terraform outputs. Alternatively, you can manually specify the name and region. If you want to use jq and do not have jq installed, install.

A. Configure GCP project andservice account

  1. Open a Terminal window.

  2. Initialize the gcloud CLI (gcloud init) to specify the GCP project you want to use. For details, see the Initializing the gcloud CLI documentation.

    💡 Tip: You do not need to configure a default Compute Region and Zone as you will specify the region.

  3. Enable the following services for your GCP project, if not already enabled:

    gcloud services enable container.googleapis.com        # For creating Kubernetes clusters
gcloud services enable sqladmin.googleapis.com         # For creating databases
gcloud services enable cloudresourcemanager.googleapis.com # For managing GCP resources
gcloud services enable servicenetworking.googleapis.com  # For private network connections
gcloud services enable iamcredentials.googleapis.com     # For security and authentication

  4. To the service account that will run the Terraform script, grant the following IAM roles:

    • roles/editor
    • roles/iam.serviceAccountAdmin
    • roles/servicenetworking.networksAdmin
    • roles/storage.admin
    • roles/container.admin

    1. Enter your GCP project ID.

      read -s PROJECT_ID

    2. Find your service account email for your GCP project

      gcloud iam service-accounts list --project $PROJECT_ID

    3. Enter your service account email.

      read -s SERVICE_ACCOUNT

    4. Grant the service account the neccessary IAM roles.

      gcloud projects add-iam-policy-binding $PROJECT_ID \
--member="serviceAccount:$SERVICE_ACCOUNT" \
--role="roles/editor"

gcloud projects add-iam-policy-binding $PROJECT_ID \
--member="serviceAccount:$SERVICE_ACCOUNT" \
--role="roles/iam.serviceAccountAdmin"

gcloud projects add-iam-policy-binding $PROJECT_ID \
--member="serviceAccount:$SERVICE_ACCOUNT" \
--role="roles/servicenetworking.networksAdmin"

gcloud projects add-iam-policy-binding $PROJECT_ID \
--member="serviceAccount:$SERVICE_ACCOUNT" \
--role="roles/storage.admin"

gcloud projects add-iam-policy-binding $PROJECT_ID \
--member="serviceAccount:$SERVICE_ACCOUNT" \
--role="roles/container.admin"

  5. For the service account, authenticate to allow Terraform to interact with your GCP project. For details, see Terraform: Google Cloud Provider Configuration reference.

    For example, if using User Application Default Credentials, you can run the following command:

    gcloud auth application-default login
    💡 Tip: If using GOOGLE_APPLICATION_CREDENTIALS, use absolute path to your key file.

B. Set up GCP Kubernetes environment and install Materialize

WARNING!

To help you get started with Materialize for evaluation purposes, Materialize provides sample Terraform modules. The sample Terraform modules are for evaluation purposes only and not intended for production use. Materialize does not support nor recommends this module for production use.

For simplicity, this tutorial stores various secrets in a file as well as prints them to the terminal. In practice, refer to your organization’s official security and Terraform/infrastructure practices.

Materialize provides sample Terraform modules for evaluation purposes only. The modules deploy a sample infrastructure on GCP (region us-central1) with the following components:

  • Google Kubernetes Engine (GKE) cluster
  • Cloud SQL PostgreSQL database for metadata storage
  • Cloud Storage bucket for blob storage
  • A dedicated VPC
  • Service accounts with proper IAM permissions
  • Materialize Operator
  • Materialize instances (during subsequent runs after the Operator is running)
💡 Tip:

The tutorial uses the module found in the examples/simple/ directory, which requires minimal user input. For more configuration options, you can run the modules at the root of the repository instead.

For details on the examples/simple/ infrastructure configuration (such as the node instance type, etc.), see the examples/simple/main.tf.

  1. Clone the Materialize’s sample Terraform repo and checkout the v0.1.7 tag. For example,

    • If cloning via SSH:

      git clone --depth 1 -b v0.1.7 git@github.com:MaterializeInc/terraform-google-materialize.git

    • If cloning via HTTPS:

      git clone --depth 1 -b v0.1.7 https://github.com/MaterializeInc/terraform-google-materialize.git

  2. Go to the examples/simple folder in the Materialize Terraform repo directory.

    cd terraform-google-materialize/examples/simple
    💡 Tip:

    The tutorial uses the module found in the examples/simple/ directory, which requires minimal user input. For more configuration options, you can run the modules at the root of the repository instead.

    For details on the examples/simple/ infrastructure configuration (such as the node instance type, etc.), see the examples/simple/main.tf.

  3. Create a terraform.tfvars file (you can copy from the terraform.tfvars.example file) and specify:

    • Your GCP project ID.

    • A prefix (e.g., mz-simple) for your resources. Prefix has a maximum of 10 characters and contains only alphanumeric characters and dashes.

    • The region for the GKE cluster.

    project_id = "enter-your-gcp-project-id"
prefix  = "enter-your-prefix" //  Maximum of 15 characters, contain lowercase alphanumeric and hyphens only (e.g., mz-simple)
region = "us-central1"

  4. Initialize the terraform directory.

    terraform init

  5. Run terraform plan and review the changes to be made.

    terraform plan

  6. If you are satisfied with the changes, apply.

    terraform apply

    To approve the changes and apply, enter yes.

    Upon successful completion, various fields and their values are output:

    Apply complete! Resources: 20 added, 0 changed, 0 destroyed.

Outputs:

connection_strings = <sensitive>
gke_cluster = <sensitive>
service_accounts = {
"gke_sa" = "mz-simple-gke-sa@my-project.iam.gserviceaccount.com"
"materialize_sa" = "mz-simple-materialize-sa@my-project.iam.gserviceaccount.com"
}

  7. Configure kubectl to connect to your EKS cluster, specifying:

    • <cluster name>. Your cluster name has the form <your prefix>-gke; e.g., mz-simple-gke.

    • <region>. By default, the example Terraform module uses the us-central1 region.

    • <project>. Your GCP project ID.

    gcloud container clusters get-credentials <cluster-name>  \
 --region <region> \
 --project <project>

    Alternatively, you can use the following command to get the cluster name and region from the Terraform output and the project ID from the environment variable set earlier.

    gcloud container clusters get-credentials $(terraform output -json gke_cluster | jq -r .name) \
 --region $(terraform output -json gke_cluster | jq -r .location) --project $PROJECT_ID

    To verify that you have configured correctly, run the following command:

    kubectl cluster-info

    For help with kubectl commands, see kubectl Quick reference.

  8. By default, the example Terraform installs the Materialize Operator. Verify the installation and check the status:

    kubectl get all -n materialize

    Wait for the components to be in the Running state:

    NAME                                                              READY       STATUS    RESTARTS   AGE
pod/materialize-mz-simple-materialize-operator-74d8f549d6-lkjjf   1/1         Running   0          36m

NAME                                                         READY       UP-TO-DATE   AVAILABLE   AGE
deployment.apps/materialize-mz-simple-materialize-operator   1/1         1            1           36m

NAME                                                                        DESIRED   CURRENT   READY   AGE
replicaset.apps/materialize-mz-simple-materialize-operator-74d8f549d6       1         1         1       36m

    If you run into an error during deployment, refer to the Troubleshooting.

  9. Once the Materialize operator is deployed and running, you can deploy the Materialize instances. To deploy Materialize instances, create a mz_instances.tfvars file with the Materialize instance configuration.

    For example, the following specifies the configuration for a demo instance.

    cat <<EOF > mz_instances.tfvars

materialize_instances = [
    {
      name           = "demo"
      namespace      = "materialize-environment"
      database_name  = "demo_db"
      cpu_request    = "1"
      memory_request = "2Gi"
      memory_limit   = "2Gi"
    }
]
EOF

  10. Run terraform plan with both .tfvars files and review the changes to be made.

    terraform plan -var-file=terraform.tfvars -var-file=mz_instances.tfvars

    The plan should show the changes to be made, with a summary similar to the following:

    Plan: 4 to add, 0 to change, 0 to destroy.

  11. If you are satisfied with the changes, apply.

    terraform apply -var-file=terraform.tfvars -var-file=mz_instances.tfvars

    To approve the changes and apply, enter yes.

    Upon successful completion, you should see output with a summary similar to the following:

    Apply complete! Resources: 4 added, 0 changed, 0 destroyed.

Outputs:

connection_strings = <sensitive>
gke_cluster = <sensitive>
service_accounts = {
  "gke_sa" = "mz-simple-gke-sa@my-project.iam.gserviceaccount.com"
  "materialize_sa" = "mz-simple-materialize-sa@my-project.iam.gserviceaccount.com"
}

  12. Verify the installation and check the status:

    kubectl get all -n materialize-environment

    Wait for the components to be in the Running state.

    NAME                                             READY   STATUS      RESTARTS      AGE
pod/create-db-demo-db-jcpnn                      0/1     Completed   0             2m11s
pod/mzpzk74xji8b-balancerd-669988bb94-5vbps      1/1     Running     0             98s
pod/mzpzk74xji8b-cluster-s2-replica-s1-gen-1-0   1/1     Running     0             96s
pod/mzpzk74xji8b-cluster-u1-replica-u1-gen-1-0   1/1     Running     0             96s
pod/mzpzk74xji8b-console-5dc9f87498-hqxdw        1/1     Running     0             91s
pod/mzpzk74xji8b-console-5dc9f87498-x95qj        1/1     Running     0             91s
pod/mzpzk74xji8b-environmentd-1-0                1/1     Running     0             113s

NAME                                               TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)                                        AGE
service/mzpzk74xji8b-balancerd                     ClusterIP   None            <none>        6876/TCP,6875/TCP                              98s
service/mzpzk74xji8b-cluster-s2-replica-s1-gen-1   ClusterIP   None            <none>        2100/TCP,2103/TCP,2101/TCP,2102/TCP,6878/TCP   97s
service/mzpzk74xji8b-cluster-u1-replica-u1-gen-1   ClusterIP   None            <none>        2100/TCP,2103/TCP,2101/TCP,2102/TCP,6878/TCP   96s
service/mzpzk74xji8b-console                       ClusterIP   None            <none>        8080/TCP                                       91s
service/mzpzk74xji8b-environmentd                  ClusterIP   None            <none>        6875/TCP,6876/TCP,6877/TCP,6878/TCP            99s
service/mzpzk74xji8b-environmentd-1                ClusterIP   None            <none>        6875/TCP,6876/TCP,6877/TCP,6878/TCP            113s
service/mzpzk74xji8b-persist-pubsub-1              ClusterIP   None            <none>        6879/TCP                                       113s

NAME                                     READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/mzpzk74xji8b-balancerd   1/1     1            1           98s
deployment.apps/mzpzk74xji8b-console     2/2     2            2           91s

NAME                                                DESIRED   CURRENT   READY      AGE
replicaset.apps/mzpzk74xji8b-balancerd-669988bb94   1         1         1          98s
replicaset.apps/mzpzk74xji8b-console-5dc9f87498     2         2         2          91s

NAME                                                        READY   AGE
statefulset.apps/mzpzk74xji8b-cluster-s2-replica-s1-gen-1   1/1     97s
statefulset.apps/mzpzk74xji8b-cluster-u1-replica-u1-gen-1   1/1     96s
statefulset.apps/mzpzk74xji8b-environmentd-1                1/1     113s

NAME                          STATUS     COMPLETIONS   DURATION   AGE
job.batch/create-db-demo-db   Complete   1/1           13s        2m11s

    If you run into an error during deployment, refer to the Troubleshooting.

  13. Open the Materialize Console in your browser:

    1. Find your console service name.

      MZ_SVC_CONSOLE=$(kubectl -n materialize-environment get svc \
  -o custom-columns="NAME:.metadata.name" --no-headers | grep console)
echo $MZ_SVC_CONSOLE

    2. Port forward the Materialize Console service to your local machine:1

      (
  while true; do
     kubectl port-forward svc/$MZ_SVC_CONSOLE 8080:8080 -n materialize-environment 2>&1 | tee /dev/stderr |
     grep -q "portforward.go" && echo "Restarting port forwarding due to an error." || break;
  done;
) &

      The command is run in background.
      - To list the background jobs, use jobs.
      - To bring back to foreground, use fg %<job-number>.
      - To kill the background job, use kill %<job-number>.

    3. Open a browser and navigate to http://localhost:8080.

    💡 Tip: If you experience long loading screens or unresponsiveness in the Materialize Console, we recommend increasing the size of the mz_catalog_server cluster. Refer to the Troubleshooting Console Unresponsiveness guide.

Next steps

  • From the Console, you can get started with the Quickstart.

  • To start ingesting your own data from an external system like Kafka, MySQL or PostgreSQL, check the documentation for sources.

Cleanup

To delete the whole sample infrastructure and deployment (including the Materialize operator and Materialize instances and data), run from the Terraform directory:

terraform destroy

When prompted to proceed, type yes to confirm the deletion.

See also

  1. The port forwarding command uses a while loop to handle a known Kubernetes issue 78446, where interrupted long-running requests through a standard port-forward cause the port forward to hang. The command automatically restarts the port forwarding if an error occurs, ensuring a more stable connection. It detects failures by monitoring for “portforward.go” error messages. ↩︎

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