Studio Lifecycle Config Args
data class StudioLifecycleConfigArgs(val studioLifecycleConfigAppType: Output<String>? = null, val studioLifecycleConfigContent: Output<String>? = null, val studioLifecycleConfigName: Output<String>? = null, val tags: Output<Map<String, String>>? = null) : ConvertibleToJava<StudioLifecycleConfigArgs>
Provides a SageMaker AI Studio Lifecycle Config resource.
Example Usage
Basic usage
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
import * as std from "@pulumi/std";
const example = new aws.sagemaker.StudioLifecycleConfig("example", {
studioLifecycleConfigName: "example",
studioLifecycleConfigAppType: "JupyterServer",
studioLifecycleConfigContent: std.base64encode({
input: "echo Hello",
}).then(invoke => invoke.result),
});
Content copied to clipboard
import pulumi
import pulumi_aws as aws
import pulumi_std as std
example = aws.sagemaker.StudioLifecycleConfig("example",
studio_lifecycle_config_name="example",
studio_lifecycle_config_app_type="JupyterServer",
studio_lifecycle_config_content=std.base64encode(input="echo Hello").result)
Content copied to clipboard
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;
using Std = Pulumi.Std;
return await Deployment.RunAsync(() =>
{
var example = new Aws.Sagemaker.StudioLifecycleConfig("example", new()
{
StudioLifecycleConfigName = "example",
StudioLifecycleConfigAppType = "JupyterServer",
StudioLifecycleConfigContent = Std.Base64encode.Invoke(new()
{
Input = "echo Hello",
}).Apply(invoke => invoke.Result),
});
});
Content copied to clipboard
package main
import (
"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
"github.com/pulumi/pulumi-std/sdk/go/std"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
invokeBase64encode, err := std.Base64encode(ctx, &std.Base64encodeArgs{
Input: "echo Hello",
}, nil)
if err != nil {
return err
}
_, err = sagemaker.NewStudioLifecycleConfig(ctx, "example", &sagemaker.StudioLifecycleConfigArgs{
StudioLifecycleConfigName: pulumi.String("example"),
StudioLifecycleConfigAppType: pulumi.String("JupyterServer"),
StudioLifecycleConfigContent: pulumi.String(invokeBase64encode.Result),
})
if err != nil {
return err
}
return nil
})
}
Content copied to clipboard
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.StudioLifecycleConfig;
import com.pulumi.aws.sagemaker.StudioLifecycleConfigArgs;
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 StudioLifecycleConfig("example", StudioLifecycleConfigArgs.builder()
.studioLifecycleConfigName("example")
.studioLifecycleConfigAppType("JupyterServer")
.studioLifecycleConfigContent(StdFunctions.base64encode(Base64encodeArgs.builder()
.input("echo Hello")
.build()).result())
.build());
}
}
Content copied to clipboard
resources:
example:
type: aws:sagemaker:StudioLifecycleConfig
properties:
studioLifecycleConfigName: example
studioLifecycleConfigAppType: JupyterServer
studioLifecycleConfigContent:
fn::invoke:
function: std:base64encode
arguments:
input: echo Hello
return: result
Content copied to clipboard
Import
Using pulumi import
, import SageMaker AI Studio Lifecycle Configs using the studio_lifecycle_config_name
. For example:
$ pulumi import aws:sagemaker/studioLifecycleConfig:StudioLifecycleConfig example example
Content copied to clipboard
Constructors
Properties
Link copied to clipboard
The App type that the Lifecycle Configuration is attached to. Valid values are JupyterServer
, JupyterLab
, CodeEditor
and KernelGateway
.
Link copied to clipboard
The content of your Studio Lifecycle Configuration script. This content must be base64 encoded.
Link copied to clipboard
The name of the Studio Lifecycle Configuration to create.