» Resource: aws_sagemaker_notebook_instance

Provides a Sagemaker Notebook Instance resource.

» Example Usage

Basic usage:

resource "aws_sagemaker_notebook_instance" "ni" {
  name          = "my-notebook-instance"
  role_arn      = "${aws_iam_role.role.arn}"
  instance_type = "ml.t2.medium"

  tags = {
    Name = "foo"

» Argument Reference

The following arguments are supported:

  • name - (Required) The name of the notebook instance (must be unique).
  • role_arn - (Required) The ARN of the IAM role to be used by the notebook instance which allows SageMaker to call other services on your behalf.
  • instance_type - (Required) The name of ML compute instance type.
  • subnet_id - (Optional) The VPC subnet ID.
  • security_groups - (Optional) The associated security groups.
  • kms_key_id - (Optional) The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
  • lifecycle_config_name - (Optional) The name of a lifecycle configuration to associate with the notebook instance.
  • tags - (Optional) A mapping of tags to assign to the resource.

» Attributes Reference

The following attributes are exported:

  • id - The name of the notebook instance.
  • arn - The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.

» Import

Sagemaker Notebook Instances can be imported using the name, e.g.

$ terraform import aws_sagemaker_notebook_instance.test_notebook_instance my-notebook-instance