Build a BigQuery processing pipeline for GKE with Eventarc

Standard

Preview — Eventarc for GKE destinations

This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms. Pre-GA features are available "as is" and might have limited support. For more information, see the launch stage descriptions.

This tutorial shows you how to use Eventarc to build a processing pipeline that schedules queries to a public BigQuery dataset, generates charts based on the data, and shares links to the charts through email.

Objectives

In this tutorial, you build and deploy three Google Kubernetes Engine (GKE) services running in a GKE cluster that receive events using Eventarc:

1. Query runner—Triggered when Cloud Scheduler jobs publish a message to a Pub/Sub topic; this service uses the BigQuery API to retrieve data from a public COVID-19 dataset, and saves the results in a new BigQuery table.
2. Chart creator—Triggered when the query runner service publishes a message to a Pub/Sub topic; this service generates charts using the Python plotting library, Matplotlib, and saves the charts to a Cloud Storage bucket.
3. Notifier—Triggered by audit logs when the chart creator service stores a chart in a Cloud Storage bucket; this service uses the email service, SendGrid, to send links of the charts to an email address.

The following diagram shows the high-level architecture:

Costs

In this document, you use the following billable components of Google Cloud:

• Artifact Registry
• BigQuery
• Cloud Build
• Cloud Scheduler
• Cloud Storage
• Eventarc
• Google Kubernetes Engine
• Pub/Sub

To generate a cost estimate based on your projected usage, use the pricing calculator.

New Google Cloud users might be eligible for a free trial.

Before you begin

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.

Install the Google Cloud CLI.

Note: If you installed the gcloud CLI previously, make sure you have the latest version by running gcloud components update.

If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

To initialize the gcloud CLI, run the following command:

gcloud init

Create or select a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

• Create a Google Cloud project:

  gcloud projects create PROJECT_ID

  Replace PROJECT_ID with a name for the Google Cloud project you are creating.

• Select the Google Cloud project that you created:

  gcloud config set project PROJECT_ID

  Replace PROJECT_ID with your Google Cloud project name.

Verify that billing is enabled for your Google Cloud project.

Enable the Artifact Registry, BigQuery, Cloud Build, Cloud Logging, Cloud Scheduler, Eventarc, GKE, Pub/Sub, and Resource Manager APIs, if any are not already enabled:

Roles required to enable APIs

To enable APIs, you need the serviceusage.services.enable permission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.

gcloud services enable artifactregistry.googleapis.com bigquery.googleapis.com cloudbuild.googleapis.com cloudresourcemanager.googleapis.com cloudscheduler.googleapis.com container.googleapis.com eventarc.googleapis.com pubsub.googleapis.com logging.googleapis.com

Install the Google Cloud CLI.

Note: If you installed the gcloud CLI previously, make sure you have the latest version by running gcloud components update.

If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

To initialize the gcloud CLI, run the following command:

gcloud init

Create or select a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

• Create a Google Cloud project:

  gcloud projects create PROJECT_ID

  Replace PROJECT_ID with a name for the Google Cloud project you are creating.

• Select the Google Cloud project that you created:

  gcloud config set project PROJECT_ID

  Replace PROJECT_ID with your Google Cloud project name.

Verify that billing is enabled for your Google Cloud project.

Enable the Artifact Registry, BigQuery, Cloud Build, Cloud Logging, Cloud Scheduler, Eventarc, GKE, Pub/Sub, and Resource Manager APIs, if any are not already enabled:

Roles required to enable APIs

To enable APIs, you need the serviceusage.services.enable permission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.

gcloud services enable artifactregistry.googleapis.com bigquery.googleapis.com cloudbuild.googleapis.com cloudresourcemanager.googleapis.com cloudscheduler.googleapis.com container.googleapis.com eventarc.googleapis.com pubsub.googleapis.com logging.googleapis.com

1. For Cloud Storage, enable audit logging for the ADMIN_READ, DATA_WRITE, and DATA_READ data access types.
   1. Read the Identity and Access Management (IAM) policy associated with your Google Cloud project, folder, or organization and store it in a temporary file:

      gcloud projects get-iam-policy PROJECT_ID > /tmp/policy.yaml

   2. In a text editor, open /tmp/policy.yaml, and add or change only the audit log configuration in the auditConfigs section:
      Caution: You must preserve the bindings: and etag: sections without changes. Changing parts of your policy not related to audit logging might make your Google Cloud project inaccessible.

      
        auditConfigs:
        - auditLogConfigs:
          - logType: ADMIN_READ
          - logType: DATA_WRITE
          - logType: DATA_READ
          service: storage.googleapis.com
        bindings:
        - members:
        [...]
        etag: BwW_bHKTV5U=
        version: 1

   3. Write your new IAM policy:

      gcloud projects set-iam-policy PROJECT_ID /tmp/policy.yaml

      If the preceding command reports a conflict with another change, then repeat these steps, starting with reading the IAM policy. For more information, see Configure Data Access audit logs with the API.

2. Set the defaults used in this tutorial:

   CLUSTER_NAME=events-cluster
   CLUSTER_LOCATION=us-central1
   PROJECT_ID=PROJECT_ID
   gcloud config set project $PROJECT_ID
   gcloud config set eventarc/location $CLUSTER_LOCATION

   Replace PROJECT_ID with your project ID.

Create a SendGrid API key

SendGrid is a cloud-based email provider that lets you send email without having to maintain email servers.

1. Sign in to SendGrid and go to Settings > API Keys.
2. Click Create API Key.
3. Select the permissions for the key. At a minimum, the key must have Mail Send permissions to send email.
4. Click Save to create the key.
5. SendGrid generates a new key. This is the only copy of the key, so make sure that you copy the key and save it for later.

Create a GKE cluster

Create a cluster with Workload Identity Federation for GKE enabled so that it can access Google Cloud services from applications running within GKE. You also need Workload Identity Federation for GKE to forward events using Eventarc.

1. Create a GKE cluster with the HttpLoadBalancing and HorizontalPodAutoscaling add-ons enabled:

   gcloud container clusters create $CLUSTER_NAME \
       --addons=HttpLoadBalancing,HorizontalPodAutoscaling \
       --machine-type=n1-standard-4 \
       --enable-autoscaling --min-nodes=2 --max-nodes=10 \
       --no-issue-client-certificate --num-nodes=2 \
       --logging=SYSTEM,WORKLOAD \
       --monitoring=SYSTEM \
       --scopes=cloud-platform,logging-write,monitoring-write,pubsub \
       --region=$CLUSTER_LOCATION \
       --release-channel=rapid \
       --workload-pool=$PROJECT_ID.svc.id.goog
   

2. Wait a few minutes for the cluster creation to complete. During the process, you might see warnings that you can safely ignore. When the cluster has been created, the output is similar to the following:

   Creating cluster ...done.
   Created [https://container.googleapis.com/v1/projects/my-project/zones/us-central1/clusters/events-cluster].
   

3. Update the kubeconfig file with credentials and endpoint information to point kubectl at the GKE cluster:

   gcloud container clusters get-credentials $CLUSTER_NAME \
       --region=$CLUSTER_LOCATION

4. Create an Artifact Registry standard repository to store your Docker container image:

   gcloud artifacts repositories create REPOSITORY \
       --repository-format=docker \
       --location=$CLUSTER_LOCATION

   Replace REPOSITORY with a unique name for the repository.

Configure the service accounts

1. To allow the GKE nodes to pull container images from Artifact Registry, grant the Artifact Registry Reader (roles/artifactregistry.reader) role on the project to the Compute Engine default service account used by the cluster nodes:

   PROJECT_NUMBER="$(gcloud projects describe $(gcloud config get-value project) --format='value(projectNumber)')"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member "serviceAccount:$[e-mail]" \
     --condition=None \
     --role "roles/artifactregistry.reader"

2. To allow the GKE services to query and write to BigQuery, publish to Pub/Sub, and upload charts to Cloud Storage, grant the BigQuery Data Editor (roles/bigquery.dataEditor), BigQuery Job User (roles/bigquery.jobUser), Pub/Sub Publisher (roles/pubsub.publisher), and Storage Object Admin (roles/storage.objectAdmin) roles on the project to the default Kubernetes ServiceAccount in the default namespace:

   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member "principal://iam.googleapis.com/projects/$PROJECT_NUMBER/locations/global/workloadIdentityPools/$PROJECT_ID.svc.id.goog/subject/ns/default/sa/default" \
     --condition=None \
     --role "roles/bigquery.dataEditor"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member "principal://iam.googleapis.com/projects/$PROJECT_NUMBER/locations/global/workloadIdentityPools/$PROJECT_ID.svc.id.goog/subject/ns/default/sa/default" \
     --condition=None \
     --role "roles/bigquery.jobUser"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member "principal://iam.googleapis.com/projects/$PROJECT_NUMBER/locations/global/workloadIdentityPools/$PROJECT_ID.svc.id.goog/subject/ns/default/sa/default" \
     --condition=None \
     --role "roles/pubsub.publisher"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
     --member "principal://iam.googleapis.com/projects/$PROJECT_NUMBER/locations/global/workloadIdentityPools/$PROJECT_ID.svc.id.goog/subject/ns/default/sa/default" \
     --condition=None \
     --role "roles/storage.objectAdmin"

Enable GKE destinations

To allow Eventarc to manage resources in the GKE cluster, enable GKE destinations and bind the Eventarc service account with the required roles.

1. Enable GKE destinations for Eventarc:

   gcloud eventarc gke-destinations init

2. At the prompt to bind the required roles, enter y.

   The following roles are bound:

   • roles/compute.viewer
   • roles/container.developer
   • roles/iam.serviceAccountAdmin

Create a Cloud Storage bucket

Create a Cloud Storage bucket in the same region as your GKE service to save the charts, and grant your account read access (roles/storage.objectViewer) to view the generated charts:

export BUCKET="$(gcloud config get-value core/project)-charts"
gcloud storage buckets create gs://${BUCKET} --location=$CLUSTER_LOCATION
gcloud storage buckets update gs://${BUCKET} --uniform-bucket-level-access
gcloud storage buckets add-iam-policy-binding gs://${BUCKET} \
    --member="user:$(gcloud config get-value core/account)" \
    --role=roles/storage.objectViewer

Note: If you send the chart links to a different email address, grant the roles/storage.objectViewer role to that recipient (--member="user:EMAIL_ADDRESS"). Granting access to a specific principal instead of allUsers complies with public access prevention.

Clone the repository

Clone the GitHub repository.

git clone https://github.com/GoogleCloudPlatform/eventarc-samples
cd eventarc-samples/processing-pipelines

Create a service account and bind access roles

Before creating the Eventarc triggers, set up a user-managed service account and grant it specific roles so that Eventarc can forward Pub/Sub events.

1. Create a service account called eventarc-triggers-test-sa:

   TRIGGER_GSA=eventarc-triggers-test-sa
   gcloud iam service-accounts create $TRIGGER_GSA

2. Grant the pubsub.subscriber, monitoring.metricWriter, and eventarc.eventReceiver roles to the service account:

   PROJECT_ID=$(gcloud config get-value project)
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
       --member "serviceAccount:$TRIGGER_GSA@$PROJECT_ID.iam.gserviceaccount.com" \
       --condition=None \
       --role "roles/pubsub.subscriber"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
       --member "serviceAccount:$TRIGGER_GSA@$PROJECT_ID.iam.gserviceaccount.com" \
       --condition=None \
       --role "roles/monitoring.metricWriter"
   
   gcloud projects add-iam-policy-binding $PROJECT_ID \
       --member "serviceAccount:$TRIGGER_GSA@$PROJECT_ID.iam.gserviceaccount.com" \
       --condition=None \
       --role "roles/eventarc.eventReceiver"

Deploy the notifier service

From the bigquery/notifier/python directory, deploy a GKE service that receives chart creator events and uses SendGrid to email links to the generated charts.

1. Build and push the container image:

   pushd bigquery/notifier/python
   export SERVICE_NAME=notifier
   docker build -t $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1 .
   docker push $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1
   popd

2. Create a Kubernetes deployment for the container image and set the required environment variables, including an address to send emails to and the SendGrid API key:

   export TO_EMAILS=EMAIL_ADDRESS
   export SENDGRID_API_KEY=YOUR_SENDGRID_API_KEY
   kubectl create deployment ${SERVICE_NAME} \
       --image=$CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1
   kubectl set env deployment/${SERVICE_NAME} \
       TO_EMAILS=${TO_EMAILS} \
       SENDGRID_API_KEY=${SENDGRID_API_KEY} \
       BUCKET=${BUCKET}

   Replace the following:

   • EMAIL_ADDRESS: an email address to send the links to the generated charts
   • YOUR_SENDGRID_API_KEY: the SendGrid API key you noted previously
   • REPOSITORY: the name of your Artifact Registry repository

3. Expose the deployment as a Kubernetes service:

   kubectl expose deployment ${SERVICE_NAME} \
       --type=ClusterIP --port=80 --target-port=8080

Note: It can take a few minutes before permissions are propagated to the service and before you can create a trigger.

Create a trigger for the notifier service

Create an Eventarc trigger for the notifier service deployed on GKE that filters for Cloud Storage audit logs for the specified Cloud Storage bucket and where the methodName is storage.objects.create:

gcloud eventarc triggers create trigger-${SERVICE_NAME}-gke \
      --destination-gke-cluster=$CLUSTER_NAME \
      --destination-gke-location=$CLUSTER_LOCATION \
      --destination-gke-namespace=default \
      --destination-gke-service=$SERVICE_NAME \
      --destination-gke-path=/ \
      --event-filters="type=google.cloud.audit.log.v1.written" \
      --event-filters="serviceName=storage.googleapis.com" \
      --event-filters="methodName=storage.objects.create" \
      --event-filters-path-pattern="resourceName=/projects/_/buckets/$BUCKET/objects/*" \
      --service-account=$TRIGGER_GSA@$PROJECT_ID.iam.gserviceaccount.com

This creates a trigger called trigger-notifier-gke.

Deploy the chart creator service

From the bigquery/chart-creator/python directory, deploy a GKE service that receives query runner events, retrieves data from a BigQuery table for a specific country, and then generates a chart, using Matplotlib, from the data. The chart is uploaded to a Cloud Storage bucket.

1. Build and push the container image:

   pushd bigquery/chart-creator/python
   export SERVICE_NAME=chart-creator
   docker build -t $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1 .
   docker push $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1
   popd

2. Create a Kubernetes deployment for the container image and set the BUCKET environment variable:

   kubectl create deployment ${SERVICE_NAME} \
       --image=$CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1
   kubectl set env deployment/${SERVICE_NAME} \
       BUCKET=${BUCKET}

3. Expose the deployment as a Kubernetes service:

   kubectl expose deployment ${SERVICE_NAME} \
       --type=ClusterIP --port=80 --target-port=8080

Create a trigger for the chart creator service

Create an Eventarc trigger for the chart creator service deployed on GKE that filters for messages published to a Pub/Sub topic.

1. Create the trigger:

   gcloud eventarc triggers create trigger-${SERVICE_NAME}-gke \
       --destination-gke-cluster=$CLUSTER_NAME \
       --destination-gke-location=$CLUSTER_LOCATION \
       --destination-gke-namespace=default \
       --destination-gke-service=$SERVICE_NAME \
       --destination-gke-path=/ \
       --event-filters="type=google.cloud.pubsub.topic.v1.messagePublished" \
       --service-account=$TRIGGER_GSA@$PROJECT_ID.iam.gserviceaccount.com

   This creates a trigger called trigger-chart-creator-gke.

2. Set the Pub/Sub topic environment variable.

   export TOPIC_QUERY_COMPLETED=$(basename $(gcloud eventarc triggers describe trigger-${SERVICE_NAME}-gke --format='value(transport.pubsub.topic)'))

Deploy the query runner service

From the processing-pipelines directory, deploy a GKE service that receives Cloud Scheduler events, retrieves data from a public COVID-19 dataset, and saves the results in a new BigQuery table.

1. Build and push the container image:

   export SERVICE_NAME=query-runner
   docker build -t $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1 -f Dockerfile .
   docker push $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1

2. Create a Kubernetes deployment for the container image and set the PROJECT_ID and TOPIC_ID environment variables:

   kubectl create deployment ${SERVICE_NAME} \
       --image=$CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/${SERVICE_NAME}:v1
   kubectl set env deployment/${SERVICE_NAME} \
       PROJECT_ID=$(gcloud config get-value project) \
       TOPIC_ID=${TOPIC_QUERY_COMPLETED}

3. Expose the deployment as a Kubernetes service:

   kubectl expose deployment ${SERVICE_NAME} \
       --type=ClusterIP --port=80 --target-port=8080

Create a trigger for the query runner service

Create an Eventarc trigger for the query runner service deployed on GKE that filters for messages published to a Pub/Sub topic.

1. Create the trigger:

   gcloud eventarc triggers create trigger-${SERVICE_NAME}-gke \
       --destination-gke-cluster=$CLUSTER_NAME \
       --destination-gke-location=$CLUSTER_LOCATION \
       --destination-gke-namespace=default \
       --destination-gke-service=$SERVICE_NAME \
       --destination-gke-path=/ \
       --event-filters="type=google.cloud.pubsub.topic.v1.messagePublished" \
       --service-account=$TRIGGER_GSA@$PROJECT_ID.iam.gserviceaccount.com

   This creates a trigger called trigger-query-runner-gke.

2. Set an environment variable for the Pub/Sub topic.

   export TOPIC_QUERY_SCHEDULED=$(basename $(gcloud eventarc triggers describe trigger-${SERVICE_NAME}-gke --format='value(transport.pubsub.topic)'))

Schedule the jobs

The processing pipeline is triggered by two Cloud Scheduler jobs. Create two Cloud Scheduler jobs that publish to a Pub/Sub topic once per day:

gcloud scheduler jobs create pubsub cre-scheduler-uk \
      --location=$CLUSTER_LOCATION \
      --schedule="0 16 * * *" \
      --topic=${TOPIC_QUERY_SCHEDULED} \
      --message-body="United Kingdom"

gcloud scheduler jobs create pubsub cre-scheduler-cy \
      --location=$CLUSTER_LOCATION \
      --schedule="0 17 * * *" \
      --topic=${TOPIC_QUERY_SCHEDULED} \
      --message-body="Cyprus"

The schedule is specified in unix-cron format. For example, 0 16 * * * means that the jobs runs at 16:00 (4 PM) UTC every day.

Run the pipeline

1. Confirm that all the triggers were successfully created:

   gcloud eventarc triggers list

   Note: It can take up to two minutes for triggers to be fully functional.

   The output should be similar to the following:

   NAME                       TYPE                                            DESTINATION         ACTIVE  LOCATION
   trigger-chart-creator-gke  google.cloud.pubsub.topic.v1.messagePublished   GKE:chart-creator   Yes     us-central1
   trigger-notifier-gke       google.cloud.audit.log.v1.written               GKE:notifier        Yes     us-central1
   trigger-query-runner-gke   google.cloud.pubsub.topic.v1.messagePublished   GKE:query-runner    Yes     us-central1
   

2. Retrieve the Cloud Scheduler job IDs:

   gcloud scheduler jobs list --location=$CLUSTER_LOCATION

   The output should be similar to the following:

   ID                LOCATION      SCHEDULE (TZ)         TARGET_TYPE  STATE
   cre-scheduler-cy  us-central1   0 17 * * * (Etc/UTC)  Pub/Sub      ENABLED
   cre-scheduler-uk  us-central1   0 16 * * * (Etc/UTC)  Pub/Sub      ENABLED
   

3. Although the jobs are scheduled to run daily at 4 and 5 PM, you can also run the Cloud Scheduler jobs manually:

   gcloud scheduler jobs run cre-scheduler-cy --location=$CLUSTER_LOCATION

   gcloud scheduler jobs run cre-scheduler-uk --location=$CLUSTER_LOCATION

4. After a few minutes, confirm that there are two charts in the Cloud Storage bucket:

   gcloud storage ls gs://${BUCKET}

   The output should be similar to the following:

   gs://PROJECT_ID-charts/chart-cyprus.png
   gs://PROJECT_ID-charts/chart-unitedkingdom.png
   

Congratulations! You should also receive two emails with links to the charts.

Clean up

If you created a new project for this tutorial, delete the project. If you used an existing project and want to keep it without the changes added in this tutorial, delete the resources created for the tutorial.

Caution: Deleting a project has the following effects:

• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.

If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects can help you avoid exceeding project quota limits.

Delete a Google Cloud project:

gcloud projects delete PROJECT_ID

Delete tutorial resources

1. Delete the Kubernetes services and deployments that you deployed in this tutorial, and delete the GKE cluster:

   kubectl delete service notifier chart-creator query-runner
   kubectl delete deployment notifier chart-creator query-runner
   gcloud container clusters delete $CLUSTER_NAME --region=$CLUSTER_LOCATION

2. Delete any Eventarc triggers you created in this tutorial:

   gcloud eventarc triggers delete TRIGGER_NAME
   

   Replace TRIGGER_NAME with the name of your trigger.

3. Delete the images from Artifact Registry:

   gcloud artifacts docker images delete $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/notifier:v1
   gcloud artifacts docker images delete $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/chart-creator:v1
   gcloud artifacts docker images delete $CLUSTER_LOCATION-docker.pkg.dev/$(gcloud config get-value project)/REPOSITORY/query-runner:v1

4. Delete the Artifact Registry repository:

   gcloud artifacts repositories delete REPOSITORY \
       --location=$CLUSTER_LOCATION

5. Delete the bucket, along with all the objects within the bucket:

   gcloud storage rm --recursive gs://${BUCKET}/

6. Delete the Cloud Scheduler jobs:

   gcloud scheduler jobs delete cre-scheduler-cy --location=$CLUSTER_LOCATION
   gcloud scheduler jobs delete cre-scheduler-uk --location=$CLUSTER_LOCATION

7. Remove any Google Cloud CLI default configurations you added during the tutorial setup:

   gcloud config unset project
   gcloud config unset eventarc/location

What's next

• Learn more about Eventarc
• Learn how to route Pub/Sub events to GKE