Execute a Cloud Run job using Workflows

---

Workflows enables you to execute Cloud Run jobs as part of a workflow to perform more complex data processing or orchestrate a system of existing jobs.

This tutorial demonstrates how to use Workflows to execute a Cloud Run job that processes data passed as environment variables to the job, in response to an event from Cloud Storage.

Note that you can also store the event data in a Cloud Storage bucket which allows you to encrypt the data using customer-managed encryption keys. For more information, see Execute a Cloud Run job that processes event data saved in Cloud Storage.

Objectives

In this tutorial you will:

1. Create a Cloud Run job that processes data files in a Cloud Storage bucket.
2. Deploy a workflow that does the following:
   1. Accepts a Cloud Storage event as an argument.
   2. Checks if the Cloud Storage bucket specified in the event is the same bucket used by the Cloud Run job.
   3. If so, uses the Cloud Run Admin API connector to execute the Cloud Run job.
3. Create an Eventarc trigger that executes the workflow in response to events affecting the Cloud Storage bucket.
4. Trigger the workflow by updating an input data file in the Cloud Storage bucket.

Costs

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

• Artifact Registry
• Cloud Build
• Cloud Run
• Cloud Storage
• Eventarc
• Workflows

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

Security constraints defined by your organization might prevent you from completing the following steps. For troubleshooting information, see Develop applications in a constrained Google Cloud environment.

Console

1. 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.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   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.

   Go to project selector

3. Make sure that billing is enabled for your Google Cloud project.

4. Enable the Artifact Registry, Cloud Build, Cloud Run, Cloud Storage, Eventarc, and Workflows APIs.

   Enable the APIs

5. Create a service account:

   1. In the Google Cloud console, go to the Create service account page.

      Go to Create service account
   2. Select your project.

   3. In the Service account name field, enter a name. The Google Cloud console fills in the Service account ID field based on this name.

      In the Service account description field, enter a description. For example, Service account for quickstart.

   4. Click Create and continue.

   5. Grant the following roles to the service account: Cloud Run Admin, Eventarc Event Receiver, Logs Writer, Workflows Invoker.

      To grant a role, find the Select a role list, then select the role.

      To grant additional roles, click Add another role and add each additional role.

      Note: The Role field affects which resources the service account can access in your project. You can revoke these roles or grant additional roles later.
   6. Click Continue.

   7. Click Done to finish creating the service account.

6. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   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.

   Go to project selector

7. Make sure that billing is enabled for your Google Cloud project.

8. Enable the Artifact Registry, Cloud Build, Cloud Run, Cloud Storage, Eventarc, and Workflows APIs.

   Enable the APIs

9. Create a service account:

   1. In the Google Cloud console, go to the Create service account page.

      Go to Create service account
   2. Select your project.

   3. In the Service account name field, enter a name. The Google Cloud console fills in the Service account ID field based on this name.

      In the Service account description field, enter a description. For example, Service account for quickstart.

   4. Click Create and continue.

   5. Grant the following roles to the service account: Cloud Run Admin, Eventarc Event Receiver, Logs Writer, Workflows Invoker.

      To grant a role, find the Select a role list, then select the role.

      To grant additional roles, click Add another role and add each additional role.

      Note: The Role field affects which resources the service account can access in your project. You can revoke these roles or grant additional roles later.
   6. Click Continue.

   7. Click Done to finish creating the service account.

10. Before creating a trigger for direct events from Cloud Storage, grant the Pub/Sub Publisher role (roles/pubsub.publisher) to the Cloud Storage service agent:
    1. In the Google Cloud console, go to the IAM page.
       

       Go to IAM

    2. Select the Include Google-provided role grants checkbox.
    3. In the Principal column, find the Cloud Storage Service Agent with the form [e-mail], and then click Edit principal in the corresponding row.
    4. Click either Add role or Add another role.
    5. In the Select a role list, filter for Pub/Sub Publisher, and then select the role.
    6. Click Save.
11. If you enabled the Cloud Pub/Sub service agent on or before April 8, 2021, to support authenticated Pub/Sub push requests, grant the Service Account Token Creator role (roles/iam.serviceAccountTokenCreator) to the service agent. Otherwise, this role is granted by default:
    1. In the Google Cloud console, go to the IAM page.
       

       Go to IAM

    2. Select the Include Google-provided role grants checkbox.
    3. In the Name column, find the Cloud Pub/Sub Service Account and then click Edit principal in the corresponding row.
    4. Click either Add role or Add another role.
    5. In the Select a role list, filter for Service Account Token Creator, and then select the role.
    6. Click Save.

12. In the Google Cloud console, activate Cloud Shell.

    Activate Cloud Shell

    At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

Cloud Shell supports the /dev/urandom commands in this tutorial that generate pseudorandom numbers.

gcloud

1. To use an online terminal with the gcloud CLI already set up, activate Cloud Shell:

   At the bottom of this page, a Cloud Shell session starts and displays a command-line prompt. It can take a few seconds for the session to initialize.

   Cloud Shell supports the /dev/urandom commands in this tutorial that generate pseudorandom numbers.

2. Create or select a Google Cloud project.

   • Create a Google Cloud project:

     gcloud projects create PROJECT_ID

   • Select the Google Cloud project that you created:

     gcloud config set project PROJECT_ID

3. Make sure that billing is enabled for your Google Cloud project.
4. Enable the Artifact Registry, Cloud Build, Cloud Run, Cloud Storage, Eventarc, and Workflows APIs:

   gcloud services enable artifactregistry.googleapis.com \
       cloudbuild.googleapis.com \
       eventarc.googleapis.com \
       run.googleapis.com \
       storage.googleapis.com \
       workflows.googleapis.com

5. Create a service account for your workflow to use for authentication with other Google Cloud services and grant it the appropriate roles.
   1. Create the service account:

      gcloud iam service-accounts create SERVICE_ACCOUNT_NAME
      

      Replace SERVICE_ACCOUNT_NAME with a name for the service account.

   2. Grant roles to the user-managed service account you created in the previous step. Run the following command once for each of the following IAM roles or you can use the --role flag multiple times in a single command:
      • roles/eventarc.eventReceiver: to receive events
      • roles/logging.logWriter: to write logs
      • roles/run.admin: to execute the Cloud Run job
      • roles/workflows.invoker: to invoke workflows

      gcloud projects add-iam-policy-binding PROJECT_ID \
          --member=serviceAccount:SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com \
          --role=ROLE
      

      Replace the following:

      • PROJECT_ID: the project ID where you created the service account
      • ROLE: the role to grant to the user-managed service account
      Note: The --role flag affects which resources your service account can access in your project. You can revoke these roles or grant additional roles later. In production environments, don't grant the Owner, Editor, or Viewer roles. Instead, grant a predefined role or custom role that meets your needs.
6. Before creating a trigger for direct events from Cloud Storage, grant the Pub/Sub Publisher role (roles/pubsub.publisher) to the Cloud Storage service agent:

   SERVICE_ACCOUNT="$(gcloud storage service-agent --project=PROJECT_ID)"
   
   gcloud projects add-iam-policy-binding PROJECT_ID \
       --member="serviceAccount:${SERVICE_ACCOUNT}" \
       --role='roles/pubsub.publisher'
   

7. If you enabled the Cloud Pub/Sub service agent on or before April 8, 2021, to support authenticated Pub/Sub push requests, grant the Service Account Token Creator role (roles/iam.serviceAccountTokenCreator) to the service agent. Otherwise, this role is granted by default:

   gcloud projects add-iam-policy-binding PROJECT_ID \
       --member=serviceAccount:[e-mail] \
       --role=roles/iam.serviceAccountTokenCreator

Replace PROJECT_NUMBER with your Google Cloud project number. You can find your project number on the Welcome page of the Google Cloud console or by running the following command:

gcloud projects describe PROJECT_ID --format='value(projectNumber)'

Terraform

1. To use an online terminal with the gcloud CLI already set up, activate Cloud Shell:

   At the bottom of this page, a Cloud Shell session starts and displays a command-line prompt. It can take a few seconds for the session to initialize.

   Cloud Shell supports the /dev/urandom commands in this tutorial that generate pseudorandom numbers.

2. Create or select a Google Cloud project.

   • Create a Google Cloud project:

     gcloud projects create PROJECT_ID

   • Select the Google Cloud project that you created:

     gcloud config set project PROJECT_ID

3. Make sure that billing is enabled for your Google Cloud project.
4. Enable the Artifact Registry, Cloud Build, Cloud Run, Cloud Storage, Eventarc, and Workflows APIs:

   gcloud services enable artifactregistry.googleapis.com \
       cloudbuild.googleapis.com \
       eventarc.googleapis.com \
       run.googleapis.com \
       storage.googleapis.com \
       workflows.googleapis.com

5. Create a service account for your workflow to use for authentication with other Google Cloud services and grant it the appropriate roles. Additionally, to support direct events from Cloud Storage, grant the Pub/Sub Publisher role (roles/pubsub.publisher) to the Cloud Storage service agent.

   Modify your main.tf file as shown in the following sample. For more information, see the Google provider for Terraform documentation.

   To learn how to apply or remove a Terraform configuration, see Basic Terraform commands.

   Note that in a typical Terraform workflow, you apply the entire plan at once. However, for the purposes of this tutorial, you can target a specific resource. For example:

   terraform apply -target="google_service_account.workflows"

   # Used to retrieve project information later
   data "google_project" "project" {}
   
   # Create a dedicated service account
   resource "google_service_account" "workflows" {
     account_id   = "workflows-run-job-sa"
     display_name = "Workflows Cloud Run Job Service Account"
   }
   
   # Grant permission to receive Eventarc events
   resource "google_project_iam_member" "eventreceiver" {
     project = data.google_project.project.id
     role    = "roles/eventarc.eventReceiver"
     member  = "serviceAccount:${google_service_account.workflows.email}"
   }
   
   # Grant permission to write logs
   resource "google_project_iam_member" "logwriter" {
     project = data.google_project.project.id
     role    = "roles/logging.logWriter"
     member  = "serviceAccount:${google_service_account.workflows.email}"
   }
   
   # Grant permission to execute Cloud Run jobs
   resource "google_project_iam_member" "runadmin" {
     project = data.google_project.project.id
     role    = "roles/run.admin"
     member  = "serviceAccount:${google_service_account.workflows.email}"
   }
   
   # Grant permission to invoke workflows
   resource "google_project_iam_member" "workflowsinvoker" {
     project = data.google_project.project.id
     role    = "roles/workflows.invoker"
     member  = "serviceAccount:${google_service_account.workflows.email}"
   }
   
   # Grant the Cloud Storage service agent permission to publish Pub/Sub topics
   data "google_storage_project_service_account" "gcs_account" {}
   resource "google_project_iam_member" "pubsubpublisher" {
     project = data.google_project.project.id
     role    = "roles/pubsub.publisher"
     member  = "serviceAccount:${data.google_storage_project_service_account.gcs_account.email_address}"
   }
   

6. If you enabled the Cloud Pub/Sub service agent on or before April 8, 2021, to support authenticated Pub/Sub push requests, grant the Service Account Token Creator role (roles/iam.serviceAccountTokenCreator) to the service agent. Otherwise, this role is granted by default:

   gcloud projects add-iam-policy-binding PROJECT_ID \
       --member=serviceAccount:[e-mail] \
       --role=roles/iam.serviceAccountTokenCreator

Replace PROJECT_NUMBER with your Google Cloud project number. You can find your project number on the Welcome page of the Google Cloud console or by running the following command:

gcloud projects describe PROJECT_ID --format='value(projectNumber)'

Create a Cloud Run job

This tutorial uses a sample Cloud Run job from GitHub. The job reads data from an input file in Cloud Storage, and performs some arbitrary processing for each line in the file.

1. Get the sample code by cloning the sample app repository to your local machine:

   git clone https://github.com/GoogleCloudPlatform/jobs-demos.git
   

   Alternatively, you can download the sample as a ZIP file and extract it.

2. Change to the directory that contains the sample code:

   cd jobs-demos/parallel-processing
   

3. Create a Cloud Storage bucket to store an input file that can be written to and trigger an event:

   Console

   1. In the Google Cloud console, go to the Cloud Storage Buckets page.
      

      Go to Buckets

   2. Click add Create.
   3. On the Create a bucket page, enter a name for your bucket:

      input-PROJECT_ID

      Replace PROJECT_ID with the ID of your Google Cloud project.
   4. Retain the other defaults.
   5. Click Create.

   gcloud

   Run the gcloud storage buckets create command:

   gcloud storage buckets create gs://input-PROJECT_ID

   If the request is successful, the command returns the following message:

   Creating gs://input-PROJECT_ID/...

   Terraform

   To create a Cloud Storage bucket, use the google_storage_bucket resource and modify your main.tf file as shown in the following sample.

   To learn how to apply or remove a Terraform configuration, see Basic Terraform commands.

   Note that in a typical Terraform workflow, you apply the entire plan at once. However, for the purposes of this tutorial, you can target a specific resource. For example:

   terraform apply -target="random_id.bucket_name_suffix"
   and
   terraform apply -target="google_storage_bucket.default"

   # Cloud Storage bucket names must be globally unique
   resource "random_id" "bucket_name_suffix" {
     byte_length = 4
   }
   
   # Create a Cloud Storage bucket
   resource "google_storage_bucket" "default" {
     name                        = "input-${data.google_project.project.name}-${random_id.bucket_name_suffix.hex}"
     location                    = "us-central1"
     storage_class               = "STANDARD"
     force_destroy               = false
     uniform_bucket_level_access = true
   }

4. Create an Artifact Registry standard repository where you can store your container image:

   Console

   1. In the Google Cloud console, go to the Artifact Registry Repositories page:

      Go to Repositories

   2. Click Create repository.

   3. Enter a name for the repository—for example, my-repo. For each repository location in a project, repository names must be unique.

   4. Retain the default format which should be Docker.

   5. Retain the default mode which should be Standard.

   6. For the region, select us-central1 (Iowa).

   7. Retain all the other defaults.

   8. Click Create.

   gcloud

   Run the command:

   gcloud artifacts repositories create REPOSITORY \
       --repository-format=docker \
       --location=us-central1

   Replace REPOSITORY with a unique name for the repository—for example, my-repo. For each repository location in a project, repository names must be unique.

   Terraform

   To create an Artifact Registry repository, use the google_artifact_registry_repository resource and modify your main.tf file as shown in the following sample.

   Note that in a typical Terraform workflow, you apply the entire plan at once. However, for the purposes of this tutorial, you can target a specific resource. For example:

   terraform apply -target="google_artifact_registry_repository.default"

   # Create an Artifact Registry repository
   resource "google_artifact_registry_repository" "default" {
     location      = "us-central1"
     repository_id = "my-repo"
     format        = "docker"
   }

5. Build the container image using a default Google Cloud buildpack:

   export SERVICE_NAME=parallel-job
   gcloud builds submit \
       --pack image=us-central1-docker.pkg.dev/PROJECT_ID/REPOSITORY/${SERVICE_NAME}
   

   Replace REPOSITORY with the name of your Artifact Registry repository.

   It can take a couple of minutes for the build to complete.

6. Create a Cloud Run job that deploys the container image:

   Console

   1. In the Google Cloud console, go to the Cloud Run page:

      Go to Cloud Run

   2. Click Create job to display the Create job form.

      1. In the form, select us-central1-docker.pkg.dev/PROJECT_ID/REPOSITORY/parallel-job:latest as the Artifact Registry container image URL.
      2. Optional: For the job name, enter parallel-job.
      3. Optional: For the region, select us-central1 (Iowa).
      4. For the number of tasks that you want to run in the job, enter 10. All of the tasks must succeed for the job to succeed. By default, the tasks execute in parallel.

   3. Expand the Container, Variables & Secrets, Connections, Security section and retain all the defaults with the exception of the following settings:

      1. Click the General tab.

         1. For the container command, enter python.
         2. For the container argument, enter process.py.

      2. Click the Variables & Secrets tab.

         1. Click Add variable, and enter INPUT_BUCKET for the name and input-PROJECT_ID for the value.
         2. Click Add variable, and enter INPUT_FILE for the name and input_file.txt for the value.

   4. To create the job, click Create.

   gcloud

   1. Set the default Cloud Run region:

      gcloud config set run/region us-central1

   2. Create the Cloud Run job:

      gcloud run jobs create parallel-job \
          --image us-central1-docker.pkg.dev/PROJECT_ID/REPOSITORY/parallel-job:latest \
          --command python \
          --args process.py \
          --tasks 10 \
          --set-env-vars=INPUT_BUCKET=input-PROJECT_ID,INPUT_FILE=input_file.txt

      Note that if you don't specify an image tag, Artifact Registry looks for the image with the default latest tag.

      For a full list of available options when creating a job, refer to the gcloud run jobs create command line documentation.

      Once the job is created, you should see a message that indicates success.

   Terraform

   To create a Cloud Run job, use the google_cloud_run_v2_job resource and modify your main.tf file as shown in the following sample.

   Note that in a typical Terraform workflow, you apply the entire plan at once. However, for the purposes of this tutorial, you can target a specific resource. For example:

   terraform apply -target="google_cloud_run_v2_job.default"

   # Create a Cloud Run job
   resource "google_cloud_run_v2_job" "default" {
     name     = "parallel-job"
     location = "us-central1"
   
     template {
       task_count = 10
       template {
         containers {
           image   = "us-central1-docker.pkg.dev/${data.google_project.project.name}/${google_artifact_registry_repository.default.repository_id}/parallel-job:latest"
           command = ["python"]
           args    = ["process.py"]
           env {
             name  = "INPUT_BUCKET"
             value = google_storage_bucket.default.name
           }
           env {
             name  = "INPUT_FILE"
             value = "input_file.txt"
           }
         }
       }
     }
   }

Deploy a workflow that executes the Cloud Run job

Define and deploy a workflow that executes the Cloud Run job you just created. A workflow definition is made up of a series of steps described using the Workflows syntax.

Console

1. In the Google Cloud console, go to the Workflows page:

   Go to Workflows

2. Click Create.

3. Enter a name for the new workflow, such as cloud-run-job-workflow.

4. For the region, select us-central1 (Iowa).

5. In the Service account field, select the service account you created earlier.

   The service account serves as the workflow's identity. You should have already granted the Cloud Run Admin role to the service account so that the workflow can execute the Cloud Run job.

6. Click Next.

7. In the workflow editor, enter the following definition for your workflow:

   main:
       params: [event]
       steps:
           - init:
               assign:
                   - project_id: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
                   - event_bucket: ${event.data.bucket}
                   - event_file: ${event.data.name}
                   - target_bucket: ${"input-" + project_id}
                   - job_name: parallel-job
                   - job_location: us-central1
           - check_input_file:
               switch:
                   - condition: ${event_bucket == target_bucket}
                     next: run_job
                   - condition: true
                     next: end
           - run_job:
               call: googleapis.run.v1.namespaces.jobs.run
               args:
                   name: ${"namespaces/" + project_id + "/jobs/" + job_name}
                   location: ${job_location}
                   body:
                       overrides:
                           containerOverrides:
                               env:
                                   - name: INPUT_BUCKET
                                     value: ${event_bucket}
                                   - name: INPUT_FILE
                                     value: ${event_file}
               result: job_execution
           - finish:
               return: ${job_execution}

8. Click Deploy.

gcloud

1. Create a source code file for your workflow:

   touch cloud-run-job-workflow.yaml
   

2. Copy the following workflow definition to your source code file:

   main:
       params: [event]
       steps:
           - init:
               assign:
                   - project_id: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
                   - event_bucket: ${event.data.bucket}
                   - event_file: ${event.data.name}
                   - target_bucket: ${"input-" + project_id}
                   - job_name: parallel-job
                   - job_location: us-central1
           - check_input_file:
               switch:
                   - condition: ${event_bucket == target_bucket}
                     next: run_job
                   - condition: true
                     next: end
           - run_job:
               call: googleapis.run.v1.namespaces.jobs.run
               args:
                   name: ${"namespaces/" + project_id + "/jobs/" + job_name}
                   location: ${job_location}
                   body:
                       overrides:
                           containerOverrides:
                               env:
                                   - name: INPUT_BUCKET
                                     value: ${event_bucket}
                                   - name: INPUT_FILE
                                     value: ${event_file}
               result: job_execution
           - finish:
               return: ${job_execution}

3. Deploy the workflow by entering the following command:

   gcloud workflows deploy cloud-run-job-workflow \
       --location=us-central1 \
       --source=cloud-run-job-workflow.yaml \
       --service-account=SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com
   

   Replace the following:

   • SERVICE_ACCOUNT_NAME: the name of the service account you created earlier
   • PROJECT_ID: the ID of your Google Cloud project

   The service account serves as the workflow's identity. You should have already granted the roles/run.admin role to the service account so that the workflow can execute the Cloud Run job.

Terraform

To create a workflow, use the google_workflows_workflow resource and modify your main.tf file as shown in the following sample.

To learn how to apply or remove a Terraform configuration, see Basic Terraform commands.

Note that in a typical Terraform workflow, you apply the entire plan at once. However, for the purposes of this tutorial, you can target a specific resource. For example:

terraform apply -target="google_workflows_workflow.default"

# Create a workflow
resource "google_workflows_workflow" "default" {
  name        = "cloud-run-job-workflow"
  region      = "us-central1"
  description = "Workflow that routes a Cloud Storage event and executes a Cloud Run job"

  # Note that $$ is needed for Terraform
  source_contents = <<EOF
  main:
      params: [event]
      steps:
          - init:
              assign:
                  - project_id: $${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
                  - event_bucket: $${event.data.bucket}
                  - event_file: $${event.data.name}
                  - target_bucket: "${google_storage_bucket.default.name}"
                  - job_name: parallel-job
                  - job_location: us-central1
          - check_input_file:
              switch:
                  - condition: $${event_bucket == target_bucket}
                    next: run_job
                  - condition: true
                    next: end
          - run_job:
              call: googleapis.run.v1.namespaces.jobs.run
              args:
                  name: $${"namespaces/" + project_id + "/jobs/" + job_name}
                  location: $${job_location}
                  body:
                      overrides:
                          containerOverrides:
                              env:
                                  - name: INPUT_BUCKET
                                    value: $${event_bucket}
                                  - name: INPUT_FILE
                                    value: $${event_file}
              result: job_execution
          - finish:
              return: $${job_execution}
  EOF
}

The workflow does the following:

1. init step—Accepts a Cloud Storage event as an argument and then sets necessary variables.

2. check_input_file step—Checks if the Cloud Storage bucket specified in the event is the bucket used by the Cloud Run job.

   • If yes, the workflow proceeds to the run_job step.
   • If no, the workflow terminates, halting any further processing.

3. run_job step—Uses the Cloud Run Admin API connector's googleapis.run.v1.namespaces.jobs.run method to execute the job. The Cloud Storage bucket and data file names are passed as override variables from the workflow to the job.

4. finish step—Returns information about the job execution as the result of the workflow.

Create an Eventarc trigger for the workflow

To automatically execute the workflow and in turn the Cloud Run job whenever the input data file is updated, create an Eventarc trigger that responds to Cloud Storage events in the bucket containing the input data file.

Console

1. In the Google Cloud console, go to the Workflows page:

   Go to Workflows

2. Click the name of your workflow, such as cloud-run-job-workflow.

3. On the Workflow details page, click Edit.

4. On the Edit workflow page, in the Triggers section, click Add new trigger > Eventarc.

   The Eventarc trigger pane opens.

5. In the Trigger name field, enter a name for the trigger, such as cloud-run-job-workflow-trigger.

6. From the Event provider list, select Cloud Storage.

7. From the Event list, select google.cloud.storage.object.v1.finalized.

8. In the Bucket field, select the bucket containing the input data file. The bucket name has the form input-PROJECT_ID.

9. In the Service account field, select the service account you created earlier.

   The service account serves as the trigger's identity. You should have already granted the following roles to the service account:

   • Eventarc Event Receiver: to receive events
   • Workflows Invoker: to execute workflows

10. Click Save trigger.

    The Eventarc trigger now appears in the Triggers section on the Edit workflow page.

11. Click Next.

12. Click Deploy.

gcloud

Create an Eventarc trigger by running the following command:

gcloud eventarc triggers create cloud-run-job-workflow-trigger \
    --location=us \
    --destination-workflow=cloud-run-job-workflow  \
    --destination-workflow-location=us-central1 \
    --event-filters="type=google.cloud.storage.object.v1.finalized" \
    --event-filters="bucket=input-PROJECT_ID" \
    --service-account=SERVICE_ACCOUNT_NAME@PROJECT_ID.iam.gserviceaccount.com

Replace the following:

• PROJECT_ID: the ID of your Google Cloud project
• SERVICE_ACCOUNT_NAME: the name of the service account you created earlier.

The service account serves as the trigger's identity. You should have already granted the following roles to the service account:

• roles/eventarc.eventReceiver: to receive events
• roles/workflows.invoker: to execute workflows

Terraform

To create a trigger, use the google_eventarc_trigger resource and modify your main.tf file as shown in the following sample.

To learn how to apply or remove a Terraform configuration, see Basic Terraform commands.

Note that in a typical Terraform workflow, you apply the entire plan at once. However, for the purposes of this tutorial, you can target a specific resource. For example:

terraform apply -target="google_eventarc_trigger.default"

# Create an Eventarc trigger that routes Cloud Storage events to Workflows
resource "google_eventarc_trigger" "default" {
  name     = "cloud-run-job-trigger"
  location = google_workflows_workflow.default.region

  # Capture objects changed in the bucket
  matching_criteria {
    attribute = "type"
    value     = "google.cloud.storage.object.v1.finalized"
  }
  matching_criteria {
    attribute = "bucket"
    value     = google_storage_bucket.default.name
  }

  # Send events to Workflows
  destination {
    workflow = google_workflows_workflow.default.id
  }

  service_account = google_service_account.workflows.email

}

Note: Although your trigger is created immediately, it can take up to two minutes for a trigger to propagate and filter events.

Whenever a file is uploaded or overwritten in the Cloud Storage bucket containing the input data file, the workflow is executed with the corresponding Cloud Storage event as an argument.

Trigger the workflow

Test the end-to-end system by updating the input data file in Cloud Storage.

1. Generate new data for the input file and upload it to Cloud Storage in the location expected by the Cloud Run job:

   base64 /dev/urandom | head -c 100000 >input_file.txt
   gcloud storage cp input_file.txt gs://input-PROJECT_ID/input_file.txt
   

   If you created a Cloud Storage bucket using Terraform, you can retrieve the name of the bucket by running the following command:

   gcloud storage buckets list gs://input*
   

   The Cloud Run job can take a few minutes to run.

2. Confirm that the Cloud Run job ran as expected by viewing the job executions:

   gcloud config set run/region us-central1
   gcloud run jobs executions list --job=parallel-job
   

   You should see a successful job execution in the output indicating that 10/10 tasks have completed.

Learn more about triggering a workflow with events or Pub/Sub messages.

Clean up

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

Delete the project

The easiest way to eliminate billing is to delete the project that you created for the tutorial.

To delete the project:

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.

1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

Delete tutorial resources

Delete the resources you created in this tutorial:

1. Delete the Eventarc trigger:

   gcloud eventarc triggers delete cloud-run-job-workflow-trigger --location=us
   

2. Delete the workflow:

   gcloud workflows delete cloud-run-job-workflow --location=us-central1
   

3. Delete the Cloud Run job:

   gcloud run jobs delete parallel-job
   

4. Delete the Cloud Storage bucket created for the input data:

   gcloud storage rm --recursive gs://input-PROJECT_ID/
   

5. Delete the Artifact Registry repository:

   gcloud artifacts repositories delete REPOSITORY --location=us-central1
   

What's next

• Learn more about Cloud Run jobs.
• Learn more about Workflows connectors.
• Learn more about Workflows.