Using the Neptune ML AWS CloudFormation template to get started quickly in a new DB cluster - Amazon Neptune

Using the Neptune ML AWS CloudFormation template to get started quickly in a new DB cluster

The easiest way to get started with Neptune ML is to use the AWS CloudFormation quick-start template. This template installs all necessary components, including a Neptune DB cluster, and sets up the necessary IAM roles.

To create the Neptune ML quick-start stack

  1. To launch the AWS CloudFormation stack on the AWS CloudFormation console, choose one of the Launch Stack buttons in the following table:

    Region View View in Designer Launch
    US East (N. Virginia) View View in Designer
    US East (Ohio) View View in Designer
    US West (N. California) View View in Designer
    US West (Oregon) View View in Designer
    Canada (Central) View View in Designer
    South America (São Paulo) View View in Designer
    Europe (Stockholm) View View in Designer
    Europe (Ireland) View View in Designer
    Europe (London) View View in Designer
    Europe (Paris) View View in Designer
    Europe (Frankfurt) View View in Designer
    Middle East (Bahrain) View View in Designer
    Africa (Cape Town) View View in Designer
    Asia Pacific (Hong Kong) View View in Designer
    Asia Pacific (Tokyo) View View in Designer
    Asia Pacific (Seoul) View View in Designer
    Asia Pacific (Singapore) View View in Designer
    Asia Pacific (Sydney) View View in Designer
    Asia Pacific (Mumbai) View View in Designer
    China (Beijing) View View in Designer
    China (Ningxia) View View in Designer
    AWS GovCloud (US-West) View View in Designer
  2. On the Select Template page, choose Next.

  3. On the Specify Details page, choose Next.

  4. On the Options page, choose Next.

  5. On the Review page, there are two check boxes that you need to check:

    • The first one acknowledges that AWS CloudFormation might create IAM resources with custom names.

    • The second acknowledges that AWS CloudFormation might require the CAPABILITY_AUTO_EXPAND capability for the new stack. CAPABILITY_AUTO_EXPAND explicitly allows AWS CloudFormation to expand macros automatically when creating the stack, without prior review.

      Customers often create a change set from a processed template so that the changes made by macros can be reviewed before actually creating the stack. For more information, see the AWS CloudFormation CreateStack API.

    Then choose Create.

The quick-start template creates and sets up the following:

  • A Neptune DB cluster.

  • The necessary IAM roles (and attaches them).

  • The necessary Amazon EC2 security group.

  • The necessary SageMaker VPC endpoints.

  • A DB cluster parameter group for Neptune ML.

  • The necessary parameters in that parameter group.

  • A SageMaker notebook with pre-populated notebook samples for Neptune ML. Note that not all instance sizes are available in every region, so you need to be sure that the notebook instance size selected is one that your region supports.

  • The Neptune-Export service.

When the quick-start stack is ready, go to the SageMaker notebook that the template created and check out the pre-populated examples. They will help you download sample datasets to use for experimenting with Neptune ML capabilities.

They can also save you a lot of time when you are using Neptune ML. For example, see the %neptune_ml line magic, and the %%neptune_ml cel magic that these notebooks support.

You can also use the following AWS CLI command to run the quick-start AWS CloudFormation template:

aws cloudformation create-stack \ --stack-name neptune-ml-fullstack-$(date '+%Y-%m-%d-%H-%M') \ --template-url https://aws-neptune-customer-samples.s3.amazonaws.com/v2/cloudformation-templates/neptune-ml-nested-stack.json \ --parameters ParameterKey=EnableIAMAuthOnExportAPI,ParameterValue=(true if you have IAM auth enabled, or false otherwise) \ ParameterKey=Env,ParameterValue=test$(date '+%H%M')\ --capabilities CAPABILITY_IAM \ --region (the AWS region, like us-east-1) \ --disable-rollback \ --profile (optionally, a named CLI profile of yours)