Manually configuring a Neptune notebook for Neptune ML - Amazon Neptune

Manually configuring a Neptune notebook for Neptune ML

Neptune SageMaker AI notebooks come pre-loaded with a variety of sample notebooks for Neptune ML. You can preview these samples in the open source graph-notebook GitHub repository.

You can use one of the existing Neptune notebooks, or if you want you can create one of your own, following the instructions in Using the Neptune workbench to host Neptune notebooks.

You can also configure a default Neptune notebook for use with Neptune ML by following these steps:

Modify a notebook for Neptune ML

  1. Open the Amazon SageMaker AI console at https://console.aws.amazon.com/sagemaker/.

  2. On the navigation pane on the left, choose Notebook, then Notebook Instances. Look for the name of the Neptune notebook that you would like to use for Neptune ML and select it to go to its details page.

  3. If the notebook instance is running, select the Stop button at the top right of the notebook details page.

  4. In Notebook instance settings, under Lifecycle Configuration, select the link to open the page for the notebook's lifecycle.

  5. Select Edit at the top right, then Continue.

  6. In the Start notebook tab, modify the script to include additional export commands and to fill in the fields for your Neptune ML IAM role and Export service URI, something like this depending on your shell:

    echo "export NEPTUNE_ML_ROLE_ARN=(your Neptune ML IAM role ARN)" >> ~/.bashrc
echo "export NEPTUNE_EXPORT_API_URI=(your export service URI)" >> ~/.bashrc

  7. Select Update.

  8. Return to the notebook instance page. Under Permissions and encryption there is a field for IAM role ARN. Select the link in this field to go to the IAM role that this notebook instance runs with.

  9. Create a new inline policy like this:

    {
  "Version": "2012-10-17",
  "Statement": [
    {
      "Action": [
        "cloudwatch:PutMetricData"
      ],
      "Resource": "arn:aws:cloudwatch:[AWS_REGION]:[AWS_ACCOUNT_ID]:*",
      "Effect": "Allow"
    },
    {
      "Action": [
        "logs:CreateLogGroup",
        "logs:CreateLogStream",
        "logs:DescribeLogStreams",
        "logs:PutLogEvents",
        "logs:GetLogEvents"
      ],
      "Resource": "arn:aws:logs:[AWS_REGION]:[AWS_ACCOUNT_ID]:*",
      "Effect": "Allow"
    },
    {
      "Action": [
        "s3:Put*",
        "s3:Get*",
        "s3:List*"
      ],
      "Resource": "arn:aws:s3:::*",
      "Effect": "Allow"
    },
    {
      "Action": "execute-api:Invoke",
      "Resource": "arn:aws:execute-api:[AWS_REGION]:[AWS_ACCOUNT_ID]:*/*",
      "Effect": "Allow"
    },
    {
      "Action": [
        "sagemaker:CreateModel",
        "sagemaker:CreateEndpointConfig",
        "sagemaker:CreateEndpoint",
        "sagemaker:DescribeModel",
        "sagemaker:DescribeEndpointConfig",
        "sagemaker:DescribeEndpoint",
        "sagemaker:DeleteModel",
        "sagemaker:DeleteEndpointConfig",
        "sagemaker:DeleteEndpoint"
      ],
      "Resource": "arn:aws:sagemaker:[AWS_REGION]:[AWS_ACCOUNT_ID]:*/*",
      "Effect": "Allow"
    },
    {
      "Action": [
        "iam:PassRole"
      ],
      "Resource": "[YOUR_NEPTUNE_ML_IAM_ROLE_ARN]"",
      "Effect": "Allow"
    }
  ]
}

  10. Save this new policy and attach it to the IAM role in Step 8.

  11. Select Start at the top right of of the SageMaker AI notebook instance details page to start the notebook instance.