# Creating Aurora zero-ETL integrations with an Amazon SageMaker lakehouse
When you create an Aurora zero-ETL integration with an Amazon SageMaker lakehouse, you specify the source Aurora DB cluster and the target Amazon Glue managed catalog. You can also customize encryption settings and add tags. Aurora creates an integration between the source DB cluster and its target. Once the integration is active, any data that you insert into the source DB cluster will be replicated into the configured target.
## Prerequisites
Before you create a zero-ETL integration with an Amazon SageMaker lakehouse, you must create a source DB cluster and a target Amazon Glue managed catalog. You also must allow replication into the catalog by adding the DB cluster as an authorized integration source.
For instructions to complete each of these steps, see [Getting started with Aurora zero-ETL integrations](zero-etl.setting-up.md).
## Required permissions
Certain IAM permissions are required to create a zero-ETL integration with an Amazon SageMaker lakehouse. At minimum, you need permissions to perform the following actions:
+ Create zero-ETL integrations for the source Aurora DB cluster.
+ View and delete all zero-ETL integrations.
+ Create inbound integrations into the target Amazon Glue managed catalog.
+ Access Amazon S3 buckets used by the Amazon Glue managed catalog.
+ Use Amazon KMS keys for encryption if custom encryption is configured.
+ Register resources with Lake Formation.
+ Put resource policy on the Amazon Glue managed catalog to authorize inbound integrations.
The following sample policy demonstrates the [least privilege permissions](https://docs.amazonaws.cn/IAM/latest/UserGuide/best-practices.html#grant-least-privilege) required to create and manage integrations with an Amazon SageMaker lakehouse. You might not need these exact permissions if your user or role has broader permissions, such as an `AdministratorAccess` managed policy.
Additionally, you must configure a resource policy on the target Amazon Glue managed catalog to authorize inbound integrations. Use the following Amazon CLI command to apply the resource policy.
### Sample Amazon CLI command to authorize inbound integrations on the target catalog
```
aws glue put-resource-policy \
--policy-in-json '{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": {
"Service": "glue.amazonaws.com"
},
"Action": [
"glue:AuthorizeInboundIntegration"
],
"Resource": ["arn:aws:glue:{{region}}:{{account_id}}:catalog/{{catalog_name}}"],
"Condition": {
"StringEquals": {
"aws:SourceArn": "arn:aws:rds:{{region}}:{{account_id}}:db:{{source_name}}"
}
}
},
{
"Effect": "Allow",
"Principal": {
"AWS": "{{account_id}}"
},
"Action": ["glue:CreateInboundIntegration"],
"Resource": ["arn:aws:glue:{{region}}:{{account_id}}:catalog/{{catalog_name}}"]
}
]
}' \
--region {{region}}
```
**Note**
Glue catalog Amazon Resource Names (ARNs) have the following format:
Glue catalog – `arn:aws:glue:{region}:{account-id}:catalog/{{catalog-name}}`
### Choosing a target Amazon Glue managed catalog in a different account
If you plan to specify a target Amazon Glue managed catalog that's in another Amazon Web Services account, you must create a role that allows users in the current account to access resources in the target account. For more information, see [Providing access to an IAM user in another Amazon Web Services account that you own](https://docs.amazonaws.cn/IAM/latest/UserGuide/id_roles_common-scenarios_aws-accounts.html).
The role must have the following permissions, which allow the user to view available Amazon Glue catalogs in the target account.
#### Required permissions and trust policy
------
#### [ JSON ]
****
```
{
"Version":"2012-10-17",
"Statement":[
{
"Effect":"Allow",
"Action":[
"glue:GetCatalog"
],
"Resource":[
"*"
]
}
]
}
```
------
The role must have the following trust policy, which specifies the target account ID.
------
#### [ JSON ]
****
```
{
"Version":"2012-10-17",
"Statement":[
{
"Effect":"Allow",
"Principal":{
"AWS": "arn:aws-cn:iam::{{111122223333}}:root"
},
"Action":"sts:AssumeRole"
}
]
}
```
------
For instructions to create the role, see [Creating a role using custom trust policies](https://docs.amazonaws.cn/IAM/latest/UserGuide/id_roles_create_for-custom.html).
## Creating zero-ETL integrations with an Amazon SageMaker lakehouse
You can create a zero-ETL integration with an Amazon SageMaker lakehouse using the Amazon Web Services Management Console, the Amazon CLI, or the RDS API.
**Important**
Zero-ETL integrations with an Amazon SageMaker lakehouse do not support refresh or resync operations. If you encounter issues with an integration after creation, you must delete the integration and create a new one.
### RDS console
**To create a zero-ETL integration with an Amazon SageMaker lakehouse**
1. Sign in to the Amazon Web Services Management Console and open the Amazon RDS console at [https://console.amazonaws.cn/rds/](https://console.amazonaws.cn/rds/).
1. In the left navigation pane, choose **Zero-ETL integrations**.
1. Choose **Create zero-ETL integration**.
1. For **Integration identifier**, enter a name for the integration. The name can have up to 63 alphanumeric characters and can include hyphens.
1. Choose **Next**.
1. For **Source**, select the Aurora DB cluster where the data will originate from.
**Note**
RDS notifies you if the DB cluster parameters aren't configured correctly. If you receive this message, you can either choose **Fix it for me**, or configure them manually. For instructions to fix them manually, see [Step 1: Create a custom DB cluster parameter group](zero-etl.setting-up.md#zero-etl.parameters).
Modifying DB cluster parameters requires a reboot. Before you can create the integration, the reboot must be complete and the new parameter values must be successfully applied to the cluster.
1. (Optional) Select **Customize data filtering options** and add data filters to your integration. You can use data filters to define the scope of replication to the target Amazon SageMaker lakehouse. For more information, see [Data filtering for Aurora zero-ETL integrations](zero-etl.filtering.md).
1. Once your source DB cluster is successfully configured, choose **Next**.
1. For **Target**, do the following:
1. (Optional) To use a different Amazon Web Services account for the Amazon SageMaker lakehouse target, choose **Specify a different account**. Then, enter the ARN of an IAM role with permissions to display your Amazon Glue catalogs. For instructions to create the IAM role, see [Choosing a target Amazon Glue managed catalog in a different account](#zero-etl.create-permissions-cross-account-smlh).
1. For **Amazon Glue catalog**, select the target for replicated data from the source DB cluster. You can choose an existing Amazon Glue managed catalog as the target.
1. The target IAM role needs describe permissions on the target catalog and must have the following permissions:
------
#### [ JSON ]
****
```
{
"Version":"2012-10-17",
"Statement": [
{
"Sid": "VisualEditor0",
"Effect": "Allow",
"Action": "glue:GetCatalog",
"Resource": [
"arn:aws-cn:glue:{{us-east-1}}:{{111122223333}}:catalog/*",
"arn:aws-cn:glue:{{us-east-1}}:{{111122223333}}:catalog"
]
}
]
}
```
------
The target IAM role must have the following trust relationship:
------
#### [ JSON ]
****
```
{
"Version":"2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "glue.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
```
------
1. You must grant the target IAM role describe permissions for the target Amazon Glue managed catalog with the Lake Formation administrator role created in [Step 3b: Create an Amazon Glue catalog for Amazon SageMaker Lakehouse zero-ETL integration](zero-etl.setting-up.md#zero-etl-setting-up.sagemaker).
**Note**
RDS notifies you if the resource policy or configuration settings for the specified Amazon Glue managed catalog aren't configured correctly. If you receive this message, you can either choose **Fix it for me**, or configure them manually.
If your selected source and target are in different Amazon Web Services accounts, then Amazon RDS cannot fix these settings for you. You must navigate to the other account and fix them manually in SageMaker Unified Studio.
1. Once your target Amazon Glue managed catalog is configured correctly, choose **Next**.
1. (Optional) For **Tags**, add one or more tags to the integration. For more information, see [Tagging Amazon Aurora andAmazon RDS resources](USER_Tagging.md).
1. For **Encryption**, specify how you want your integration to be encrypted. By default, RDS encrypts all integrations with an Amazon owned key. To choose a customer managed key instead, enable **Customize encryption settings** and choose a KMS key to use for encryption. For more information, see [Encrypting Amazon Aurora resources](Overview.Encryption.md).
Optionally, add an encryption context. For more information, see [Encryption context](https://docs.amazonaws.cn/kms/latest/developerguide/concepts.html#encrypt_context) in the *Amazon Key Management Service Developer Guide*.
**Note**
Amazon RDS adds the following encryption context pairs in addition to any that you add:
`aws:glue:integration:arn` - `IntegrationArn`
`aws:servicename:id` - `glue`
This reduces the overall number of pairs that you can add from 8 to 6, and contributes to the overall character limit of the grant constraint. For more information, see [Using grant constraints](https://docs.amazonaws.cn/kms/latest/developerguide/create-grant-overview.html#grant-constraints) in the *Amazon Key Management Service Developer Guide*.
1. Choose **Next**.
1. Review your integration settings and choose **Create zero-ETL integration**.
If creation fails, see [Troubleshooting Aurora zero-ETL integrations](zero-etl.troubleshooting.md) for troubleshooting steps.
The integration has a status of `Creating` while it's being created, and the target Amazon SageMaker lakehouse has a status of `Modifying`. During this time, you can't query the catalog or make any configuration changes on it.
When the integration is successfully created, the status of the integration and the target Amazon SageMaker lakehouse both change to `Active`.
### Amazon CLI
To prepare a target Amazon Glue managed catalog for zero-ETL integration using the Amazon CLI, you must first use the [create-integration-resource-property](https://docs.amazonaws.cn/cli/latest/reference/rds/create-integration.html) command with the following options:
+ `--resource-arn` – Specify the ARN of the Amazon Glue managed catalog that will be the target for the integration.
+ `--target-processing-properties` – Specify the ARN of the IAM role to access the target Amazon Glue managed catalog
```
aws glue create-integration-resource-property --region us-east-1
--resource-arn arn:aws:glue:{{region}}:{{account_id}}:catalog/{{catalog_name}} \
--target-processing-properties '{"RoleArn" : "arn:aws:iam::{{account_id}}:role/TargetIamRole"}'
```
To create a zero-ETL integration with an Amazon SageMaker lakehouse using the Amazon CLI, use the [create-integration](https://docs.amazonaws.cn/cli/latest/reference/rds/create-integration.html) command with the following options:
+ `--integration-name` – Specify a name for the integration.
+ `--source-arn` – Specify the ARN of the Aurora DB cluster that will be the source for the integration.
+ `--target-arn` – Specify the ARN of the Amazon Glue managed catalog that will be the target for the integration.
**Example**
For Linux, macOS, or Unix:
```
aws rds create-integration \
--integration-name {{my-sagemaker-integration}} \
--source-arn arn:aws:rds:{{{region}}}:{{{account-id}}}:{{cluster:my-db}} \
--target-arn arn:aws:glue:{{{region}}}:{{{account-id}}}:catalog/{{catalog-name}}
```
For Windows:
```
aws rds create-integration ^
--integration-name {{my-sagemaker-integration}} ^
--source-arn arn:aws:rds:{{{region}}}:{{{account-id}}}:{{cluster:my-db}} ^
--target-arn arn:aws:glue:{{{region}}}:{{{account-id}}}:catalog/{{catalog-name}}
```
### RDS API
To create a zero-ETL integration with Amazon SageMaker by using the Amazon RDS API, use the [https://docs.amazonaws.cn/AmazonRDS/latest/APIReference/API_CreateIntegration.html](https://docs.amazonaws.cn/AmazonRDS/latest/APIReference/API_CreateIntegration.html) operation with the following parameters:
**Note**
Catalog names are limited to 19 characters. Ensure your IntegrationName parameter meets this requirement if it will be used as a catalog name.
+ `IntegrationName` – Specify a name for the integration.
+ `SourceArn` – Specify the ARN of the Aurora DB cluster that will be the source for the integration.
+ `TargetArn` – Specify the ARN of the Amazon Glue managed catalog that will be the target for the integration.
## Encrypting integrations with a customer managed key
If you specify a custom KMS key rather than an Amazon owned key when you create an integration with Amazon SageMaker, the key policy must provide the SageMaker Unified Studio service principal access to the `CreateGrant` action. In addition, it must allow the current user to perform to the `DescribeKey` and `CreateGrant` actions.
The following sample policy demonstrates how to provide the required permissions in the key policy. It includes context keys to further reduce the scope of permissions.
### Sample key policy
------
#### [ JSON ]
****
```
{
"Version":"2012-10-17",
"Id": "Key policy",
"Statement": [
{
"Sid": "EnablesIAMUserPermissions",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws-cn:iam::{{111122223333}}:root"
},
"Action": "kms:*",
"Resource": "*"
},
{
"Sid": "GlueServicePrincipalAddGrant",
"Effect": "Allow",
"Principal": {
"Service": "glue.amazonaws.com"
},
"Action": "kms:CreateGrant",
"Resource": "*",
"Condition": {
"StringEquals": {
"kms:EncryptionContext:{{{context-key}}}":"{{{context-value}}}"
},
"ForAllValues:StringEquals": {
"kms:GrantOperations": [
"Decrypt",
"GenerateDataKey",
"CreateGrant"
]
}
}
},
{
"Sid": "AllowsCurrentUserRoleAddGrantKMSKey",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws-cn:iam::{{111122223333}}:role/{{{role-name}}}"
},
"Action": "kms:CreateGrant",
"Resource": "*",
"Condition": {
"StringEquals": {
"kms:EncryptionContext:{{{context-key}}}":"{{{context-value}}}",
"kms:ViaService": "rds.us-east-1.amazonaws.com"
},
"ForAllValues:StringEquals": {
"kms:GrantOperations": [
"Decrypt",
"GenerateDataKey",
"CreateGrant"
]
}
}
},
{
"Sid": "AllowsCurrentUserRoleRetrieveKMSKeyInformation",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws-cn:iam::{{111122223333}}:role/{{{role-name}}}"
},
"Action": "kms:DescribeKey",
"Resource": "*"
}
]
}
```
------
For more information, see [Creating a key policy](https://docs.amazonaws.cn/kms/latest/developerguide/key-policy-overview.html) in the *Amazon Key Management Service Developer Guide*.
## Next steps
After you successfully create a zero-ETL integration with Amazon SageMaker, you can start adding data to the source Aurora DB cluster and querying it in your Amazon SageMaker lakehouse. The data will be automatically replicated and made available for analytics and machine learning workloads.