Step 1. Launch the stack - Maintaining Personalized Experiences with Machine Learning

Step 1. Launch the stack

This automated AWS CloudFormation template deploys the Maintaining Personalized Experiences with Machine Learning solution in the AWS Cloud.

Note

You are responsible for the cost of the AWS services used while running this AWS solution. For more details, visit the Cost section in this guide, and refer to the pricing webpage for each AWS service used in this solution.

  1. Sign in to the AWS Management Console and select the button to launch the maintaining-personalized-experiences-with-machine-learning.template AWS CloudFormation template.

    Solution launch button

  2. The template launches in the US East (N. Virginia) Region by default. To launch the AWS solution in a different AWS Region, use the Region selector in the console navigation bar.

    Note

    This AWS solution uses the Amazon Personalize service, which is not currently available in all AWS Regions. You must launch this solution in an AWS Region where Amazon Personalize is available. For the most current availability by Region, refer to the AWS Regional Services List.

  3. On the Create stack page, verify that the correct template URL is in the Amazon S3 URL text box and choose Next.

  4. On the Specify stack details page, assign a name to your AWS solution stack. For information about naming character limitations, refer to IAM and STS Limits in the AWS Identity and Access Management User Guide.

  5. Under Parameters, review the parameters for this AWS solution template and modify them as necessary. This AWS solution uses the following default values.

    Parameter Default Description
    Email <Optional input> The email that receives status notifications from the AWS Step Functions state machines deployed by this solution. If this parameter is blank, you are not notified with your personalization maintenance job results. You must accept the SNS subscription (through the email link that is sent after stack deployment) to activate notifications.
    Personalize KMS Key ARN <Optional input>

    While Amazon Personalize will encrypt your data by default, you can monitor and restrict access to your data by specifying a KMS key in your account that can be used by the Amazon Personalize service. Specifying an AWS KMS key ARN in this parameter allows Amazon Personalize to use that key to protect your data.

    Revoking, turning off, or modifying the key policy associated with this key may render your data unusable by the Amazon Personalize service.

    To use your own key, specify the full key ARN, for example: arn:aws:kms:<region>:<account_id>:key/f8fed2cd-14ab-4ac4-a8a3-57975cbff81b.

    The key policy must grant the personalize service Encrypt, Decrypt, GenerateDataKey, and DescribeKey permissions on the key, as well as turn on user permissions for the key. An example key policy can be found in KMS customer-managed key policy.

    Leave this parameter blank to have Amazon Personalize use its default encryption configuration for your data.

  6. Choose Next.

  7. On the Configure stack options page, choose Next.

  8. On the Review and create page, review and confirm the settings. Check the box acknowledging that the template will create AWS Identity and Access Management (IAM) resources.

  9. Choose Submit to deploy the stack.

    You can view the status of the stack in the AWS CloudFormation Console in the Status column. You should receive a CREATE_COMPLETE status in approximately five minutes.

Note

In addition to the primary AWS Lambda functions used to create and maintain Amazon Personalize resources, this AWS solution includes additional Lambda functions, that run only during initial configuration or when resources are updated or deleted.

When you run this AWS solution, you will notice Lambda functions with the stack name you used as a prefix in the AWS console. You must not delete any of these functions, as they are necessary to manage associated resources.