Table: gcp_vertex_ai_notebook_runtime_template - Query GCP Vertex AI Notebook Runtime Templates using SQL

Google Cloud Vertex AI Notebook Runtime Templates provide preconfigured environments for machine learning workloads. These templates allow you to define runtime settings such as machine type, networking, disk storage, and more. The gcp_vertex_ai_notebook_runtime_template table in Steampipe allows you to query detailed information about Notebook Runtime Templates, including network configurations, service account settings, and machine specifications.

Table Usage Guide

The gcp_vertex_ai_notebook_runtime_template table helps cloud administrators, data scientists, and machine learning engineers gather insights into their Vertex AI Notebook Runtime Templates. You can query the configuration settings for machine specs, network access, disk storage, and more. This table is particularly useful for monitoring resource usage, managing templates, and ensuring that the runtime environment meets your workload needs.

Examples

Basic info

Retrieve basic information about the Notebook Runtime Templates, including their name, location, and creation time.

select
  name,
  display_name,
  location,
  create_time,
  is_default
from
  gcp_vertex_ai_notebook_runtime_template;

select
  name,
  display_name,
  location,
  create_time,
  is_default
from
  gcp_vertex_ai_notebook_runtime_template;

List templates by machine type

Identify templates that are using a specific machine type, such as "e2-standard-4".

select
  name,
  display_name,
  machine_spec ->> 'machine_type' as machine_type,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  machine_spec ->> 'machine_type' = 'e2-standard-4';

select
  name,
  display_name,
  json_extract(machine_spec, '$.machine_type') as machine_type,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  json_extract(machine_spec, '$.machine_type') = 'e2-standard-4';

List templates with internet access enabled

Retrieve templates that have internet access enabled in their network configuration.

select
  name,
  network_spec ->> 'enable_internet_access' as internet_access,
  network_spec ->> 'network' as network,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  network_spec ->> 'enable_internet_access' = 'true';

select
  name,
  json_extract(network_spec, '$.enable_internet_access') as internet_access,
  json_extract(network_spec, '$.network') as network,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  json_extract(network_spec, '$.enable_internet_access') = 'true';

List templates by disk size

Identify templates with specific persistent disk sizes, which is useful for understanding storage configurations.

select
  name,
  data_persistent_disk_spec ->> 'disk_size_gb' as disk_size_gb,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  data_persistent_disk_spec ->> 'disk_size_gb' = '10';

select
  name,
  json_extract(data_persistent_disk_spec, '$.disk_size_gb') as disk_size_gb,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  json_extract(data_persistent_disk_spec, '$.disk_size_gb') = '10';

List templates by tag

Retrieve templates associated with specific tags for organizational purposes.

select
  name,
  display_name,
  tags ->> 'foo' as tag_value,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  tags ->> 'foo' = 'bar';

select
  name,
  display_name,
  json_extract(tags, '$.foo') as tag_value,
  location
from
  gcp_vertex_ai_notebook_runtime_template
where
  json_extract(tags, '$.foo') = 'bar';

This table is available as a standalone Exporter CLI. Steampipe exporters are stand-alone binaries that allow you to extract data using Steampipe plugins without a database.

You can download the tarball for your platform from the Releases page, but it is simplest to install them with the steampipe_export_installer.sh script:

/bin/sh -c "$(curl -fsSL https://steampipe.io/install/export.sh)" -- gcp

You can pass the configuration to the command with the --config argument:

steampipe_export_gcp --config '<your_config>' gcp_vertex_ai_notebook_runtime_template,md