# Set Default Lifecycle Configurations for Amazon SageMaker Studio Classic
**Important**
As of November 30, 2023, the previous Amazon SageMaker Studio experience is now named Amazon SageMaker Studio Classic. The following section is specific to using the Studio Classic application. For information about using the updated Studio experience, see [Amazon SageMaker Studio](studio-updated.md).
Studio Classic is still maintained for existing workloads but is no longer available for onboarding. You can only stop or delete existing Studio Classic applications and cannot create new ones. We recommend that you [migrate your workload to the new Studio experience](studio-updated-migrate.md).
Although you can attach multiple lifecycle configuration scripts to a single resource, you can only set one default lifecycle configuration for each JupyterServer or KernelGateway application. The behavior of the default lifecycle configuration depends on whether it is set for JupyterServer or KernelGateway apps.
+ **JupyterServer apps:** When set as the default lifecycle configuration script for JupyterServer apps, the lifecycle configuration script runs automatically when the user signs in to Studio Classic for the first time or restarts Studio Classic. Use this default lifecycle configuration to automate one-time setup actions for the Studio Classic developer environment, such as installing notebook extensions or setting up a GitHub repo. For an example of this, see [Customize Amazon SageMaker Studio using Lifecycle Configurations](https://aws.amazon.com/blogs/machine-learning/customize-amazon-sagemaker-studio-using-lifecycle-configurations/).
+ **KernelGateway apps:** When set as the default lifecycle configuration script for KernelGateway apps, the lifecycle configuration is selected by default in the Studio Classic launcher. Users can launch a notebook or terminal with the default script selected, or they can select a different one from the list of lifecycle configurations.
SageMaker AI supports setting a default lifecycle configuration for the following resources:
+ Domains
+ User profiles
+ Shared spaces
While domains and user profiles support setting a default lifecycle configuration from both the Amazon SageMaker AI console and AWS Command Line Interface, shared spaces only support setting a default lifecycle configuration from the AWS CLI.
You can set a lifecycle configuration as the default when creating a new resource or updating an existing resource. The following topics demonstrate how to set a default lifecycle configuration using the SageMaker AI console and AWS CLI.
## Default lifecycle configuration inheritance
Default lifecycle configurations set at the *domain* level are inherited by all users and shared spaces. Default lifecycle configurations set at the *user* and *shared space* level are scoped to only that user or shared space. User and space defaults override defaults set at the domain level.
A default KernelGateway lifecycle configuration set for a domain applies to all KernelGateway applications launched in the domain. Unless the user selects a different lifecycle configuration from the list presented in the Studio Classic launcher, the default lifecycle configuration is used. The default script also runs if `No Script` is selected by the user. For more information about selecting a script, see [Step 3: Launch an application with the lifecycle configuration](studio-lcc-create-console.md#studio-lcc-create-console-step3).
**Topics**
+ [Default lifecycle configuration inheritance](#studio-lcc-defaults-inheritance)
+ [Set Defaults from the AWS CLI for Amazon SageMaker Studio Classic](studio-lcc-defaults-cli.md)
+ [Set Defaults from the SageMaker AI Console for Amazon SageMaker Studio Classic](studio-lcc-defaults-console.md)
# Set Defaults from the AWS CLI for Amazon SageMaker Studio Classic
**Important**
Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see [Provide permissions for tagging SageMaker AI resources](security_iam_id-based-policy-examples.md#grant-tagging-permissions).
[AWS managed policies for Amazon SageMaker AI](security-iam-awsmanpol.md) that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.
**Important**
As of November 30, 2023, the previous Amazon SageMaker Studio experience is now named Amazon SageMaker Studio Classic. The following section is specific to using the Studio Classic application. For information about using the updated Studio experience, see [Amazon SageMaker Studio](studio-updated.md).
Studio Classic is still maintained for existing workloads but is no longer available for onboarding. You can only stop or delete existing Studio Classic applications and cannot create new ones. We recommend that you [migrate your workload to the new Studio experience](studio-updated-migrate.md).
You can set default lifecycle configuration scripts from the AWS CLI for the following resources:
+ Domains
+ User profiles
+ Shared spaces
The following sections outline how to set default lifecycle configuration scripts from the AWS CLI.
**Topics**
+ [Prerequisites](#studio-lcc-defaults-cli-prereq)
+ [Set a default lifecycle configuration when creating a new resource](#studio-lcc-defaults-cli-new)
+ [Set a default lifecycle configuration for an existing resource](#studio-lcc-defaults-cli-existing)
## Prerequisites
Before you begin, complete the following prerequisites:
+ Update the AWS CLI by following the steps in [Installing the current AWS CLI version](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv1.html#install-tool-bundled).
+ From your local machine, run `aws configure` and provide your AWS credentials. For information about AWS credentials, see [Understanding and getting your AWS credentials](https://docs.aws.amazon.com/general/latest/gr/aws-sec-cred-types.html).
+ Onboard to SageMaker AI domain by following the steps in [Amazon SageMaker AI domain overview](gs-studio-onboard.md).
+ Create a lifecycle configuration following the steps in [Create and Associate a Lifecycle Configuration with Amazon SageMaker Studio Classic](studio-lcc-create.md).
## Set a default lifecycle configuration when creating a new resource
To set a default lifecycle configuration when creating a new domain, user profile, or space, pass the ARN of your previously created lifecycle configuration as part of one of the following AWS CLI commands:
+ [create-user-profile](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/sagemaker/create-user-profile.html)
+ [create-domain](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/opensearch/create-domain.html)
+ [create-space](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/sagemaker/create-space.html)
You must pass the lifecycle configuration ARN for the following values in the KernelGateway or JupyterServer default settings:
+ `DefaultResourceSpec`:`LifecycleConfigArn` - This specifies the default lifecycle configuration for the application type.
+ `LifecycleConfigArns` - This is the list of all lifecycle configurations attached to the application type. The default lifecycle configuration must also be part of this list.
For example, the following API call creates a new user profile with a default lifecycle configuration.
```
aws sagemaker create-user-profile --domain-id domain-id \
--user-profile-name user-profile-name \
--region region \
--user-settings '{
"KernelGatewayAppSettings": {
"DefaultResourceSpec": {
"InstanceType": "ml.t3.medium",
"LifecycleConfigArn": "lifecycle-configuration-arn"
},
"LifecycleConfigArns": [lifecycle-configuration-arn-list]
}
}'
```
## Set a default lifecycle configuration for an existing resource
To set or update the default lifecycle configuration for an existing resource, pass the ARN of your previously created lifecycle configuration as part of one of the following AWS CLI commands:
+ [update-user-profile](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/sagemaker/update-user-profile.html)
+ [update-domain](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/sagemaker/update-domain.html)
+ [update-space](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/sagemaker/update-space.html)
You must pass the lifecycle configuration ARN for the following values in the KernelGateway or JupyterServer default settings:
+ `DefaultResourceSpec`:`LifecycleConfigArn` - This specifies the default lifecycle configuration for the application type.
+ `LifecycleConfigArns` - This is the list of all lifecycle configurations attached to the application type. The default lifecycle configuration must also be part of this list.
For example, the following API call updates a user profile with a default lifecycle configuration.
```
aws sagemaker update-user-profile --domain-id domain-id \
--user-profile-name user-profile-name \
--region region \
--user-settings '{
"KernelGatewayAppSettings": {
"DefaultResourceSpec": {
"InstanceType": "ml.t3.medium",
"LifecycleConfigArn": "lifecycle-configuration-arn"
},
"LifecycleConfigArns": [lifecycle-configuration-arn-list]
}
}'
```
The following API call updates a domain to set a new default lifecycle configuration.
```
aws sagemaker update-domain --domain-id domain-id \
--region region \
--default-user-settings '{
"JupyterServerAppSettings": {
"DefaultResourceSpec": {
"InstanceType": "system",
"LifecycleConfigArn": "lifecycle-configuration-arn"
},
"LifecycleConfigArns": [lifecycle-configuration-arn-list]
}
}'
```
# Set Defaults from the SageMaker AI Console for Amazon SageMaker Studio Classic
**Important**
Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see [Provide permissions for tagging SageMaker AI resources](security_iam_id-based-policy-examples.md#grant-tagging-permissions).
[AWS managed policies for Amazon SageMaker AI](security-iam-awsmanpol.md) that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.
**Important**
As of November 30, 2023, the previous Amazon SageMaker Studio experience is now named Amazon SageMaker Studio Classic. The following section is specific to using the Studio Classic application. For information about using the updated Studio experience, see [Amazon SageMaker Studio](studio-updated.md).
Studio Classic is still maintained for existing workloads but is no longer available for onboarding. You can only stop or delete existing Studio Classic applications and cannot create new ones. We recommend that you [migrate your workload to the new Studio experience](studio-updated-migrate.md).
You can set default lifecycle configuration scripts from the SageMaker AI console for the following resources.
+ Domains
+ User profiles
You cannot set default lifecycle configuration scripts for shared spaces from the SageMaker AI console. For information about setting defaults for shared spaces, see [Set Defaults from the AWS CLI for Amazon SageMaker Studio Classic](studio-lcc-defaults-cli.md).
The following sections outline how to set default lifecycle configuration scripts from the SageMaker AI console.
**Topics**
+ [Prerequisites](#studio-lcc-defaults-cli-prerequisites)
+ [Set a default lifecycle configuration for a domain](#studio-lcc-defaults-cli-domain)
+ [Set a default lifecycle configuration for a user profile](#studio-lcc-defaults-cli-user-profile)
## Prerequisites
Before you begin, complete the following prerequisites:
+ Onboard to SageMaker AI domain by following the steps in [Amazon SageMaker AI domain overview](gs-studio-onboard.md).
+ Create a lifecycle configuration following the steps in [Create and Associate a Lifecycle Configuration with Amazon SageMaker Studio Classic](studio-lcc-create.md).
## Set a default lifecycle configuration for a domain
The following procedure shows how to set a default lifecycle configuration for a domain from the SageMaker AI console.
1. Open the Amazon SageMaker AI console at [https://console.aws.amazon.com/sagemaker/](https://console.aws.amazon.com/sagemaker/).
1. From the list of domains, select the name of the domain to set the default lifecycle configuration for.
1. From the **Domain details** page, choose the **Environment** tab.
1. Under **Lifecycle configurations for personal Studio apps**, select the lifecycle configuration that you want to set as the default for the domain. You can set distinct defaults for JupyterServer and KernelGateway applications.
1. Choose **Set as default**. This opens a pop up window that lists the current defaults for JupyterServer and KernelGateway applications.
1. Choose **Set as default** to set the lifecycle configuration as the default for its respective application type.
## Set a default lifecycle configuration for a user profile
The following procedure shows how to set a default lifecycle configuration for a user profile from the SageMaker AI console.
1. Open the Amazon SageMaker AI console at [https://console.aws.amazon.com/sagemaker/](https://console.aws.amazon.com/sagemaker/).
1. From the list of domains, select the name of the domain that contains the user profile that you want to set the default lifecycle configuration for.
1. From the **Domain details** page, choose the **User profiles** tab.
1. Select the name of the user profile to set the default lifecycle configuration for. This opens a **User Details** page.
1. From the **User Details** page, choose **Edit**. This opens an **Edit user profile** page.
1. From the **Edit user profile** page, choose **Step 2 Studio settings**.
1. Under **Lifecycle configurations attached to user**, select the lifecycle configuration that you want to set as the default for the user profile. You can set distinct defaults for JupyterServer and KernelGateway applications.
1. Choose **Set as default**. This opens a pop up window that lists the current defaults for JupyterServer and KernelGateway applications.
1. Choose **Set as default** to set the lifecycle configuration as the default for its respective application type.