1. IAM User Policies for SageMaker Notebook Authentication

    Python

    To create IAM user policies specifically for authenticating to a SageMaker Notebook instance, you'll need to define an IAM policy that grants access to the necessary SageMaker operations, and then attach that policy to the IAM user. This process involves using two main AWS resources: aws.iam.Policy and aws.iam.UserPolicyAttachment.

    Here's a step-by-step guide to what this Pulumi program does:

    1. Define an IAM Policy: Specify the permissions that the user needs to interact with SageMaker Notebooks. This includes actions like creating, accessing, and deleting notebook instances.
    2. Create the IAM User: If not already present, create the IAM user who will be working with SageMaker.
    3. Attach the Policy to the User: Attach the newly created IAM policy to the user to grant them the defined permissions.

    Below is a Pulumi program written in Python that carries out these steps:

    import pulumi import pulumi_aws as aws # Define the IAM policy with required permissions for SageMaker Notebook sagemaker_policy = aws.iam.Policy("sagemakerPolicy", # A policy document that specifies the permissions policy={ "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": [ "sagemaker:CreateNotebookInstance", "sagemaker:DescribeNotebookInstance", "sagemaker:DeleteNotebookInstance", "sagemaker:StartNotebookInstance", "sagemaker:StopNotebookInstance", "sagemaker:UpdateNotebookInstance" ], "Resource": "*" }] }) # Define an IAM user for SageMaker Notebook sagemaker_user = aws.iam.User("sagemakerUser") # Attach the policy to the IAM User sagemaker_attach_policy = aws.iam.UserPolicyAttachment("sagemakerAttachPolicy", user=sagemaker_user.name, # Reference the SageMaker user policy_arn=sagemaker_policy.arn # Reference the SageMaker policy ARN ) # Export the user's name and policy ARN for reference pulumi.export("sagemaker_user_name", sagemaker_user.name) pulumi.export("sagemaker_policy_arn", sagemaker_policy.arn)

    Explanation:

    • aws.iam.Policy('sagemakerPolicy', ...): This creates a new IAM policy with the provided policy document. The document details the permissions the user will have, centered around SageMaker Notebook operations.

    • aws.iam.User('sagemakerUser', ...): This creates a new IAM user. In practice, you can replace the "sagemakerUser" string with your desired IAM username. If the user already exists, you don't need to create one and can attach the policy to the existing user.

    • aws.iam.UserPolicyAttachment('sagemakerAttachPolicy', ...): This attaches the IAM policy to the user. It specifies which user to attach the policy to and points to the ARN (Amazon Resource Name) of the IAM policy.

    • pulumi.export(...): This part of the Pulumi program makes the IAM user's name and policy ARN available as stack outputs once the program runs successfully. These outputs can be helpful for reference or integration with other systems.

    To run this program, you'll need to have Pulumi installed and configured for AWS access. You would typically execute the command pulumi up in the directory where this Python file is located to deploy the resources to your AWS account. Make sure you've also set up the appropriate AWS credentials.