1. VPC Endpoint-Powered Secure SageMaker Studio Access


    To create a VPC Endpoint-powered secure SageMaker Studio access, we will define a Pulumi program that provisions the necessary AWS resources including a VPC, subnets, security groups, and a VPC endpoint for SageMaker Runtime. Additionally, we'll ensure that the networking is configured correctly for SageMaker Studio to access AWS resources securely within the VPC.

    In the following Pulumi program written in Python, we'll use the pulumi_aws package to define our resources:

    1. VPC: This is a virtual network within AWS that is isolated from other virtual networks. It enables you to launch AWS resources into a network that you define.
    2. Subnets: These are subdivisions within a VPC that can be isolated from each other for organizational or security purposes.
    3. Security Group: It acts as a virtual firewall for associated AWS resources to control inbound and outbound traffic.
    4. VPC Endpoint: A VPC endpoint enables private connections between your VPC and AWS services without requiring an internet gateway, NAT device, VPN connection, or AWS Direct Connect connection.

    Here's a program that accomplishes this:

    import pulumi import pulumi_aws as aws # Create a new VPC for SageMaker studio to ensure network isolation vpc = aws.ec2.Vpc("sagemaker_studio_vpc", cidr_block="", enable_dns_hostnames=True, enable_dns_support=True) # Create subnet for SageMaker Studio subnet = aws.ec2.Subnet("sagemaker_studio_subnet", vpc_id=vpc.id, cidr_block="", availability_zone="us-west-2a") # Change this to your preferred AZ # Create a security group for the VPC endpoint sagemaker_security_group = aws.ec2.SecurityGroup("sagemaker_sec_grp", vpc_id=vpc.id, description="Allow SageMaker to communicate within VPC", egress=[aws.ec2.SecurityGroupEgressArgs( from_port=0, to_port=0, protocol="-1", # This specifies all protocols cidr_blocks=[""], )], ingress=[aws.ec2.SecurityGroupIngressArgs( from_port=443, to_port=443, protocol="tcp", cidr_blocks=[vpc.cidr_block], )]) # Create a VPC endpoint for SageMaker Runtime sagemaker_endpoint = aws.ec2.VpcEndpoint("sagemaker_runtime_vpc_endpoint", vpc_id=vpc.id, service_name="com.amazonaws.us-west-2.sagemaker.runtime", vpc_endpoint_type="Interface", subnet_ids=[subnet.id], security_group_ids=[sagemaker_security_group.id]) # Export the VPC and VPC endpoint IDs pulumi.export("vpc_id", vpc.id) pulumi.export("sagemaker_endpoint_id", sagemaker_endpoint.id)

    In the above program, we start by creating a new VPC where our SageMaker Studio will operate. We configure a subnet within the VPC where the SageMaker Studio can be hosted. We situate the subnet in a specific availability zone for redundancy and low-latency access. We can replicate this setup across multiple availability zones for higher availability.

    The security group is set up to allow outgoing traffic to all destinations and incoming HTTPS traffic from within the VPC. Adjust these rules as necessary to fit your organization's security policies.

    Finally, we define a VPC endpoint for the SageMaker Runtime service. This is an interface endpoint, meaning it is a network interface within our VPC that serves as an entry point for traffic destined to SageMaker Runtime.

    After running this program with Pulumi, the output will provide the VPC ID and VPC endpoint ID, which can be utilized to configure your SageMaker Studio environment securely within this new network infrastructure.