Medium: Managing your GCP inventory with Cloud Asset API (export_assets)

main.py

import base64
from google.cloud import asset_v1

def export_assets(event, context):
    # create client
    client = asset_v1.AssetServiceClient()
    print("""This Function was triggered by messageId {} published at {} to {}
    """.format(context.event_id, context.timestamp, context.resource["name"]))
    
    # bq partition spec
    # PARTITION_KEY_UNSPECIFIED = 0
    # READ_TIME = 1
    # REQUEST_TIME = 2
    partition_spec = asset_v1.PartitionSpec()
    partition_spec.partition_key = 1
    
    # init request
    output_config = asset_v1.OutputConfig()
    output_config.bigquery_destination.dataset = "projects/myproject-123/datasets/cloud_assets"
    output_config.bigquery_destination.table = "data"
    output_config.bigquery_destination.force = True
    output_config.bigquery_destination.parition_spec = partition_spec
    
    request = asset_v1.ExportAssetsRequest(
        parent = "projects/myproject-123",
        content_type = "RESOURCE",
        asset_types = [
            ".*.googleapis.com.*Cluster",
            ".*.googleapis.com.*Instance",
            "cloudfunctions.googleapis.com/CloudFunction",             
            "compute.googleapis.com/ForwardingRule",
            "compute.googleapis.com/VpnTunnel",
            "container.googleapis.com.*",
            "iam.googleapis.com.*",
            "storage.googleapis.com/Bucket",
        ],
        output_config = output_config,
    )
    
    # make request
    operation = client.export_assets(request=request)
    
    msg_body = base64.b64decode(event['data']).decode('utf-8')
    print('Exporting: {}'.format(msg_body))
    response = operation.result()
    
    # handle response
    print(response)