Table: aws_sagemaker_app - Query AWS SageMaker App using SQL

The AWS SageMaker App is a component of Amazon SageMaker that provides a platform for developers and data scientists to build, train, and deploy machine learning models quickly. It offers a fully managed service that covers the entire machine learning workflow to label and prepare your data, choose an algorithm, train the model, tune and optimize it for deployment, make predictions, and take action. SageMaker App simplifies the process of building, training, and deploying machine learning models, allowing you to get your models to production faster with much less effort and at lower cost.

Table Usage Guide

The aws_sagemaker_app table in Steampipe provides you with information about AWS SageMaker Apps. This table enables you, as a DevOps engineer, data scientist, or other technical professional, to query application-specific details, including resource names, ARNs, types, statuses, and creation times. You can utilize this table to gather insights on SageMaker Apps, such as their configurations, user settings, and more. The schema outlines the various attributes of the SageMaker App for you, including the app ARN, creation time, status, and associated tags.

Examples

Basic info

Explore the status and creation time of your AWS Sagemaker apps to understand their current operational state and longevity. This can aid in resource management and troubleshooting.

select
  name,
  arn,
  creation_time,
  status
from
  aws_sagemaker_app;

select
  name,
  arn,
  creation_time,
  status
from
  aws_sagemaker_app;

List apps that failed to create

Discover the segments that failed during the application creation process within AWS SageMaker. This is useful to understand and rectify issues that prevent successful application creation.

select
  name,
  arn,
  creation_time,
  status,
  failure_reason
from
  aws_sagemaker_app
where
  status = 'Failed';

select
  name,
  arn,
  creation_time,
  status,
  failure_reason
from
  aws_sagemaker_app
where
  status = 'Failed';

Schema for aws_sagemaker_app

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
account_id	text	=, !=, ~~, ~~, !~~, !~~	The AWS Account ID in which the resource is located.
akas	jsonb		Array of globally unique identifier strings (also known as) for the resource.
app_type	text	=	The type of app.
arn	text		The Amazon Resource Name (ARN) of the app.
creation_time	timestamp with time zone		A timestamp that indicates when the app was created.
domain_id	text	=	The domain ID.
failure_reason	text		The failure reason.
last_health_check_timestamp	timestamp with time zone		The timestamp of the last health check.
last_user_activity_timestamp	timestamp with time zone		The timestamp of the last user activity.
name	text	=	The app name.
partition	text		The AWS partition in which the resource is located (aws, aws-cn, or aws-us-gov).
region	text		The AWS Region in which the resource is located.
resource_spec	jsonb		The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
sp_connection_name	text	=, !=, ~~, ~~, !~~, !~~	Steampipe connection name.
sp_ctx	jsonb		Steampipe context in JSON form.
space_name	text		The name of the space. If this value is not set, then UserProfileName must be set.
status	text		The status of the app.
title	text		Title of the resource.
user_profile_name	text	=	The user profile name.

Export

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)" -- aws

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

steampipe_export_aws --config '<your_config>' aws_sagemaker_app