Deactivating AWS environments created with reduced permissions mode
Learn how to deactivate an environment that has been activated for use in Cloudera Data Warehouse (CDW) with the reduced permissions mode. When you deactivate an environment in CDW, the environment registered with CDP remains available for use by other applications.
If a CDP environment has been activated for CDW with the reduced permissions mode, then if you deactivate the environment in the CDW UI, you must manually delete the CloudFormation stack in AWS and its associated S3 buckets and DynamoDB table. After you click the deactivation icon in the CDW environment tile, a link displays in the tile that you can use to navigate to the AWS Console to delete these cloud resources.
- In the CDW UI, navigate to the tile for the environment you want to deactivate, and click the deactivation icon (), which launches the Action dialog box.
(Optional) In the Action dialog box, you can select one of
the following environment deactivation options if appropriate:
- Choose Drop Data if you want to drop any data CDW created outside of the Data Lake, but retain the Database Catalogs and Virtual Warehouses that are associated with the environment.
- Choose Force Delete if you want to drop the data and also remove the Database Catalogs and Virtual Warehouses that are associated with the environment.
- Click Visit AWS Console to Delete Stack, which displays in the Action dialog box. This opens the AWS Console in another browser tab.
- In the Action dialog box of the CDW UI, click OK, and then wait five minutes so CDW can perform its deletion steps.
- After waiting five minutes, in the AWS Console, click Delete to delete the CloudFormation stack in your AWS account.
In the AWS Console, perform the following tasks:
Navigate to the S3 service and delete the following S3 buckets that were used by
sales-eastand the CDW environment ID is
ENV-CK8988, the buckets you should delete are:
- Navigate to the DynamoDB service and delete the associated DynamoDB table.
- Navigate to the S3 service and delete the following S3 buckets that were used by the stack: