cloud-workflows-demo

This repository contains demo data-pipelines orchestrated by Google Cloud Workflows.

Pipelines:

• Word Count (event driven processing)
  • Text files arrives to a GCS bucket
  • Object notification is sent to PubSub
  • PubSub push-subscription triggers a Cloud Function
  • Cloud Function triggers a Cloud Workflow with the necessary arguments
  • Cloud Workflow encapsulates all steps to process this file and execute them:
    • Submits a serverless Spark job to Dataproc. The job count the words and store the results per file in a BigQuery table
    • Pool the job status and wait to report success or failure
    • If the Spark job succeeds, it triggers a SQL step to BigQuery to re-construct an aggreagte table

All resources are defined and deployed by a Terraform module.

Terraform Deployment

Set Variables

export PROJECT_ID=
export COMPUTE_REGION=
export ACCOUNT=user@company.com
export BUCKET=${PROJECT_ID}-terraform
export TF_SA=terraform

Create (or activate) a gcloud account for that project

export CONFIG=workflows-sandbox
gcloud config configurations create $CONFIG

gcloud config set project $PROJECT_ID
gcloud config set account $ACCOUNT
gcloud config set compute/region $COMPUTE_REGION

Auth gcloud

gcloud auth login --project $PROJECT_ID
gcloud auth application-default login --project $PROJECT_ID

Prepare Terraform State Bucket

gsutil mb -p $PROJECT_ID -l $COMPUTE_REGION -b on gs://$BUCKET

Prepare Terraform Service Account

Terraform needs to run with a service account to deploy DLP resources. User accounts are not enough.

./scripts/prepare_terraform_service_account.sh

Enable GCP APIs

./scripts/enable_gcp_apis.sh

Terraform Variables Configuration

The solution is deployed by Terraform and thus all configurations are done on the Terraform side.

Create a Terraform .tfvars file

Create a new .tfvars file and override the variables in the below sections. You can use the example tfavrs files as a base example-variables.

export VARS=variables.tfvars

Configure Project Variables

Most required variables have default values defined in variables.tf. One can use the defaults or overwrite them in the newly created .tfvars.

Both ways, one must set the below variables:

project = "<GCP project ID to deploy solution to (equals to $PROJECT_ID) >"
compute_region = "<GCP region to deploy compute resources e.g. cloud run, iam, etc (equals to $COMPUTE_REGION)>"
data_region = "<GCP region to deploy data resources (buckets, datasets, tag templates, etc> (equals to $DATA_REGION)"

Configure Terraform Service Account

Terraform needs to run with a service account to deploy DLP resources. User accounts are not enough.

This service account name is defined in the "Setup Environment Variables" step and created in the "Prepare Terraform Service Account" step. Use the full email of the created account.

terraform_service_account = "${TF_SA}@${PROJECT_ID}.iam.gserviceaccount.com"

Deploy Terraform

Terraform needs to run with a service account to deploy DLP resources. User accounts are not enough.

./scripts/deploy_terraform.sh

Enable Google Private Access

• This repo is using the default VPC of the target project
• To use Dataproc with private IPs one must enable Google Private Access on the subnetwork. This is done via

gcloud compute networks subnets update <SUBNETWORK> \
--region=<REGION> \
--enable-private-ip-google-access

• On the customer project, a shared VPC is expected and the subnetwork has to enable Google Private Access

Running Sample

To execute the wordcount pipeline, upload a text file to the data bucket created by Terraform

gsutil cp gs://pub/shakespeare/rose.txt gs://<project>-data-wordcount/landing/rose.txt

The wordcount Cloud Workflow will populate BigQuery tables sandbox.word_count_output and sandbox.word_count_aggregate

Run the below query to track the progress of file processing steps across the different GCP components:

SELECT * FROM monitoring.v_global_tracker