How to add Network settings (VPC, Security Group, Subnet) when configuring new Notebook Job in SageMaker Studio - JupyterLab?

1. Use an Existing VPC and Subnet in the Domain Settings

SageMaker Studio is set up within a specific VPC and subnets during the initial domain setup. If your Redshift cluster is within the same VPC, your notebook should be able to connect without additional configuration.

Ensure that the security group associated with your SageMaker Studio domain allows outbound access to your Redshift cluster.

2. Configure IAM Role with Required Permissions

Ensure that the IAM role attached to the SageMaker Studio instance has the necessary permissions to access Amazon Redshift. This includes permissions for Redshift and any other AWS services you might need.

3. Using Lifecycle Configurations

You can use a SageMaker Studio Lifecycle Configuration (LCC) to set environment variables or install dependencies when the notebook starts. While this doesn't directly set the VPC, subnet, or security group, it allows you to prepare the environment for network connections as needed.

4. Running the Notebook with Parameters (Advanced)

In the "Parameters" field of the Notebook Job configuration, you can pass custom environment variables or other configurations that your notebook can use.

If you want to pass VPC, Subnet, or Security Group information this way, you would need to modify your notebook to read these parameters and adjust its behavior accordingly. However, this is not a typical approach since network settings are usually managed at the infrastructure level rather than in the notebook itself.

5. Accessing Redshift from SageMaker Studio

If your SageMaker Studio is properly set up within the correct VPC and has the necessary IAM permissions, you should be able to connect to Redshift from within your notebook using the usual methods (psycopg2, SQLAlchemy, etc.). If you're encountering connection issues, double-check the security group rules, ensuring that inbound rules allow traffic from the SageMaker Studio's IP address range to Redshift's endpoint.

6. Alternative: Use SageMaker Notebook Instances

If you need more control over network settings, consider using SageMaker Notebook Instances instead of Studio. When creating a Notebook Instance, you can directly specify the VPC, Subnet, and Security Groups.

Example of Connecting to Redshift in Your Notebook:

import psycopg2

# Replace with your Redshift cluster details
conn = psycopg2.connect(
    dbname='your_db_name',
    user='your_username',
    password='your_password',
    host='your_redshift_cluster_endpoint',
    port='5439'
)

cur = conn.cursor()
cur.execute("SELECT * FROM your_table;")
rows = cur.fetchall()

for row in rows:
    print(row)

cur.close()
conn.close()

If your Studio domain and Redshift cluster are properly configured within the same VPC, and security group rules are correct, this code should work without requiring additional network configuration.

Hello,

When configuring a Notebook Job in SageMaker Studio, you cannot directly specify VPC, Security Group, or Subnet settings via the UI. Instead, you can associate your SageMaker domain with a specific VPC, and the Notebook Job will inherit those settings. The "Parameters" field is not for setting network configurations.

To ensure your Notebook Job can connect to Redshift, you should:

1. Associate SageMaker Domain with VPC: Ensure your SageMaker domain is associated with a VPC that has access to your Redshift cluster.

2. Configure Security Groups and Subnets: Attach the necessary Security Group and Subnet to your SageMaker domain. This will allow the Notebook Job to run within the specified network settings.

check document for referral: https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html

Well, that's the confusing part. I added the necessary conditions to the domain and still got Redshift connection error (connection timed out). I attach screenshots with both SageMaker Domain and Redshift properties:

1. SageMaker domain:
2. Redshift: