aws-cdk.aws-redshift 1.131.0

The CDK Construct Library for AWS::Redshift

Amazon Redshift Construct Library

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All classes with the Cfn prefix in this module (CFN Resources) are always stable and safe to use.

The APIs of higher level constructs in this module are experimental and under active development. They are subject to non-backward compatible changes or removal in any future version. These are not subject to the Semantic Versioning model and breaking changes will be announced in the release notes. This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.

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Starting a Redshift Cluster Database

To set up a Redshift cluster, define a Cluster. It will be launched in a VPC. You can specify a VPC, otherwise one will be created. The nodes are always launched in private subnets and are encrypted by default.

# Example automatically generated. See https://github.com/aws/jsii/issues/826
import aws_cdk.aws_ec2 as ec2


vpc = ec2.Vpc(self, "Vpc")
cluster = Cluster(self, "Redshift",
    master_user=Login(
        master_username="admin"
    ),
    vpc=vpc
)

By default, the master password will be generated and stored in AWS Secrets Manager.

A default database named default_db will be created in the cluster. To change the name of this database set the defaultDatabaseName attribute in the constructor properties.

By default, the cluster will not be publicly accessible. Depending on your use case, you can make the cluster publicly accessible with the publiclyAccessible property.

Connecting

To control who can access the cluster, use the .connections attribute. Redshift Clusters have a default port, so you don't need to specify the port:

# Example automatically generated. See https://github.com/aws/jsii/issues/826
cluster.connections.allow_default_port_from_any_ipv4("Open to the world")

The endpoint to access your database cluster will be available as the .clusterEndpoint attribute:

# Example automatically generated. See https://github.com/aws/jsii/issues/826
cluster.cluster_endpoint.socket_address

Rotating credentials

When the master password is generated and stored in AWS Secrets Manager, it can be rotated automatically:

# Example automatically generated. See https://github.com/aws/jsii/issues/826
cluster.add_rotation_single_user()

The multi user rotation scheme is also available:

# Example automatically generated. See https://github.com/aws/jsii/issues/826
import aws_cdk.aws_secretsmanager as secretsmanager


cluster.add_rotation_multi_user("MyUser",
    secret=secretsmanager.Secret.from_secret_name_v2(self, "Imported Secret", "my-secret")
)

Database Resources

This module allows for the creation of non-CloudFormation database resources such as users and tables. This allows you to manage identities, permissions, and stateful resources within your Redshift cluster from your CDK application.

Because these resources are not available in CloudFormation, this library leverages custom resources to manage them. In addition to the IAM permissions required to make Redshift service calls, the execution role for the custom resource handler requires database credentials to create resources within the cluster.

These database credentials can be supplied explicitly through the adminUser properties of the various database resource constructs. Alternatively, the credentials can be automatically pulled from the Redshift cluster's default administrator credentials. However, this option is only available if the password for the credentials was generated by the CDK application (ie., no value vas provided for the masterPassword property of Cluster.masterUser).

Creating Users

Create a user within a Redshift cluster database by instantiating a User construct. This will generate a username and password, store the credentials in a AWS Secrets Manager Secret, and make a query to the Redshift cluster to create a new database user with the credentials.

# Example automatically generated. See https://github.com/aws/jsii/issues/826
User(self, "User",
    cluster=cluster,
    database_name="databaseName"
)

By default, the user credentials are encrypted with your AWS account's default Secrets Manager encryption key. You can specify the encryption key used for this purpose by supplying a key in the encryptionKey property.

# Example automatically generated. See https://github.com/aws/jsii/issues/826
import aws_cdk.aws_kms as kms


encryption_key = kms.Key(self, "Key")
User(self, "User",
    encryption_key=encryption_key,
    cluster=cluster,
    database_name="databaseName"
)

By default, a username is automatically generated from the user construct ID and its path in the construct tree. You can specify a particular username by providing a value for the username property. Usernames must be valid identifiers; see: Names and identifiers in the Amazon Redshift Database Developer Guide.

# Example automatically generated. See https://github.com/aws/jsii/issues/826
User(self, "User",
    username="myuser",
    cluster=cluster,
    database_name="databaseName"
)

The user password is generated by AWS Secrets Manager using the default configuration found in secretsmanager.SecretStringGenerator, except with password length 30 and some SQL-incompliant characters excluded. The plaintext for the password will never be present in the CDK application; instead, a CloudFormation Dynamic Reference will be used wherever the password value is required.

Creating Tables

Create a table within a Redshift cluster database by instantiating a Table construct. This will make a query to the Redshift cluster to create a new database table with the supplied schema.

# Example automatically generated. See https://github.com/aws/jsii/issues/826
Table(self, "Table",
    table_columns=[Column(name="col1", data_type="varchar(4)"), Column(name="col2", data_type="float")],
    cluster=cluster,
    database_name="databaseName"
)

Granting Privileges

You can give a user privileges to perform certain actions on a table by using the Table.grant() method.

# Example automatically generated. See https://github.com/aws/jsii/issues/826
user = User(self, "User",
    cluster=cluster,
    database_name="databaseName"
)
table = Table(self, "Table",
    table_columns=[Column(name="col1", data_type="varchar(4)"), Column(name="col2", data_type="float")],
    cluster=cluster,
    database_name="databaseName"
)

table.grant(user, TableAction.DROP, TableAction.SELECT)

Take care when managing privileges via the CDK, as attempting to manage a user's privileges on the same table in multiple CDK applications could lead to accidentally overriding these permissions. Consider the following two CDK applications which both refer to the same user and table. In application 1, the resources are created and the user is given INSERT permissions on the table:

# Example automatically generated. See https://github.com/aws/jsii/issues/826
database_name = "databaseName"
username = "myuser"
table_name = "mytable"

user = User(self, "User",
    username=username,
    cluster=cluster,
    database_name=database_name
)
table = Table(self, "Table",
    table_columns=[Column(name="col1", data_type="varchar(4)"), Column(name="col2", data_type="float")],
    cluster=cluster,
    database_name=database_name
)
table.grant(user, TableAction.INSERT)

In application 2, the resources are imported and the user is given INSERT permissions on the table:

# Example automatically generated. See https://github.com/aws/jsii/issues/826
database_name = "databaseName"
username = "myuser"
table_name = "mytable"

user = User.from_user_attributes(self, "User",
    username=username,
    password=SecretValue.plain_text("NOT_FOR_PRODUCTION"),
    cluster=cluster,
    database_name=database_name
)
table = Table.from_table_attributes(self, "Table",
    table_name=table_name,
    table_columns=[Column(name="col1", data_type="varchar(4)"), Column(name="col2", data_type="float")],
    cluster=cluster,
    database_name="databaseName"
)
table.grant(user, TableAction.INSERT)

Both applications attempt to grant the user the appropriate privilege on the table by submitting a GRANT USER SQL query to the Redshift cluster. Note that the latter of these two calls will have no effect since the user has already been granted the privilege.

Now, if application 1 were to remove the call to grant, a REVOKE USER SQL query is submitted to the Redshift cluster. In general, application 1 does not know that application 2 has also granted this permission and thus cannot decide not to issue the revocation. This leads to the undesirable state where application 2 still contains the call to grant but the user does not have the specified permission.

Note that this does not occur when duplicate privileges are granted within the same application, as such privileges are de-duplicated before any SQL query is submitted.