Notebook Instance Args
Provides a SageMaker AI Notebook Instance resource.
Example Usage
Basic usage
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
const ni = new aws.sagemaker.NotebookInstance("ni", {
name: "my-notebook-instance",
roleArn: role.arn,
instanceType: "ml.t2.medium",
tags: {
Name: "foo",
},
});
import pulumi
import pulumi_aws as aws
ni = aws.sagemaker.NotebookInstance("ni",
name="my-notebook-instance",
role_arn=role["arn"],
instance_type="ml.t2.medium",
tags={
"Name": "foo",
})
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;
return await Deployment.RunAsync(() =>
{
var ni = new Aws.Sagemaker.NotebookInstance("ni", new()
{
Name = "my-notebook-instance",
RoleArn = role.Arn,
InstanceType = "ml.t2.medium",
Tags =
{
{ "Name", "foo" },
},
});
});
package main
import (
"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := sagemaker.NewNotebookInstance(ctx, "ni", &sagemaker.NotebookInstanceArgs{
Name: pulumi.String("my-notebook-instance"),
RoleArn: pulumi.Any(role.Arn),
InstanceType: pulumi.String("ml.t2.medium"),
Tags: pulumi.StringMap{
"Name": pulumi.String("foo"),
},
})
if err != nil {
return err
}
return nil
})
}
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.NotebookInstance;
import com.pulumi.aws.sagemaker.NotebookInstanceArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var ni = new NotebookInstance("ni", NotebookInstanceArgs.builder()
.name("my-notebook-instance")
.roleArn(role.arn())
.instanceType("ml.t2.medium")
.tags(Map.of("Name", "foo"))
.build());
}
}
resources:
ni:
type: aws:sagemaker:NotebookInstance
properties:
name: my-notebook-instance
roleArn: ${role.arn}
instanceType: ml.t2.medium
tags:
Name: foo
Code repository usage
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
const example = new aws.sagemaker.CodeRepository("example", {
codeRepositoryName: "my-notebook-instance-code-repo",
gitConfig: {
repositoryUrl: "https://github.com/github/docs.git",
},
});
const ni = new aws.sagemaker.NotebookInstance("ni", {
name: "my-notebook-instance",
roleArn: role.arn,
instanceType: "ml.t2.medium",
defaultCodeRepository: example.codeRepositoryName,
tags: {
Name: "foo",
},
});
import pulumi
import pulumi_aws as aws
example = aws.sagemaker.CodeRepository("example",
code_repository_name="my-notebook-instance-code-repo",
git_config={
"repository_url": "https://github.com/github/docs.git",
})
ni = aws.sagemaker.NotebookInstance("ni",
name="my-notebook-instance",
role_arn=role["arn"],
instance_type="ml.t2.medium",
default_code_repository=example.code_repository_name,
tags={
"Name": "foo",
})
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;
return await Deployment.RunAsync(() =>
{
var example = new Aws.Sagemaker.CodeRepository("example", new()
{
CodeRepositoryName = "my-notebook-instance-code-repo",
GitConfig = new Aws.Sagemaker.Inputs.CodeRepositoryGitConfigArgs
{
RepositoryUrl = "https://github.com/github/docs.git",
},
});
var ni = new Aws.Sagemaker.NotebookInstance("ni", new()
{
Name = "my-notebook-instance",
RoleArn = role.Arn,
InstanceType = "ml.t2.medium",
DefaultCodeRepository = example.CodeRepositoryName,
Tags =
{
{ "Name", "foo" },
},
});
});
package main
import (
"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
example, err := sagemaker.NewCodeRepository(ctx, "example", &sagemaker.CodeRepositoryArgs{
CodeRepositoryName: pulumi.String("my-notebook-instance-code-repo"),
GitConfig: &sagemaker.CodeRepositoryGitConfigArgs{
RepositoryUrl: pulumi.String("https://github.com/github/docs.git"),
},
})
if err != nil {
return err
}
_, err = sagemaker.NewNotebookInstance(ctx, "ni", &sagemaker.NotebookInstanceArgs{
Name: pulumi.String("my-notebook-instance"),
RoleArn: pulumi.Any(role.Arn),
InstanceType: pulumi.String("ml.t2.medium"),
DefaultCodeRepository: example.CodeRepositoryName,
Tags: pulumi.StringMap{
"Name": pulumi.String("foo"),
},
})
if err != nil {
return err
}
return nil
})
}
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.CodeRepository;
import com.pulumi.aws.sagemaker.CodeRepositoryArgs;
import com.pulumi.aws.sagemaker.inputs.CodeRepositoryGitConfigArgs;
import com.pulumi.aws.sagemaker.NotebookInstance;
import com.pulumi.aws.sagemaker.NotebookInstanceArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var example = new CodeRepository("example", CodeRepositoryArgs.builder()
.codeRepositoryName("my-notebook-instance-code-repo")
.gitConfig(CodeRepositoryGitConfigArgs.builder()
.repositoryUrl("https://github.com/github/docs.git")
.build())
.build());
var ni = new NotebookInstance("ni", NotebookInstanceArgs.builder()
.name("my-notebook-instance")
.roleArn(role.arn())
.instanceType("ml.t2.medium")
.defaultCodeRepository(example.codeRepositoryName())
.tags(Map.of("Name", "foo"))
.build());
}
}
resources:
example:
type: aws:sagemaker:CodeRepository
properties:
codeRepositoryName: my-notebook-instance-code-repo
gitConfig:
repositoryUrl: https://github.com/github/docs.git
ni:
type: aws:sagemaker:NotebookInstance
properties:
name: my-notebook-instance
roleArn: ${role.arn}
instanceType: ml.t2.medium
defaultCodeRepository: ${example.codeRepositoryName}
tags:
Name: foo
Import
Using pulumi import
, import SageMaker AI Notebook Instances using the name
. For example:
$ pulumi import aws:sagemaker/notebookInstance:NotebookInstance test_notebook_instance my-notebook-instance
Constructors
Properties
A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium
, ml.eia1.large
, ml.eia1.xlarge
, ml.eia2.medium
, ml.eia2.large
, ml.eia2.xlarge
.
An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in AWS CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in AWS CodeCommit or in any other Git repository.
Set to Disabled
to disable internet access to notebook. Requires security_groups
and subnet_id
to be set. Supported values: Enabled
(Default) or Disabled
. If set to Disabled
, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration
. see details below.
The name of ML compute instance type.
The name of a lifecycle configuration to associate with the notebook instance.
The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1
, notebook-al2-v1
, notebook-al2-v2
, or notebook-al2-v3
, depending on which version of Amazon Linux you require.
Whether root access is Enabled
or Disabled
for users of the notebook instance. The default value is Enabled
.
The associated security groups.
The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.