aws-cdk.aws-redshift 1.204.0

Description:

awscdk.awsredshift 1.204.0

Amazon Redshift Construct Library
---


AWS CDK v1 has reached End-of-Support on 2023-06-01.
This package is no longer being updated, and users should migrate to AWS CDK v2.
For more information on how to migrate, see the Migrating to AWS CDK v2 guide.



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.
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:
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:
cluster.cluster_endpoint.socket_address

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.
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.
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.
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.
Table(self, "Table",
table_columns=[Column(name="col1", data_type="varchar(4)"), Column(name="col2", data_type="float")],
cluster=cluster,
database_name="databaseName"
)

The table can be configured to have distStyle attribute and a distKey column:
Table(self, "Table",
table_columns=[Column(name="col1", data_type="varchar(4)", dist_key=True), Column(name="col2", data_type="float")
],
cluster=cluster,
database_name="databaseName",
dist_style=TableDistStyle.KEY
)

The table can also be configured to have sortStyle attribute and sortKey columns:
Table(self, "Table",
table_columns=[Column(name="col1", data_type="varchar(4)", sort_key=True), Column(name="col2", data_type="float", sort_key=True)
],
cluster=cluster,
database_name="databaseName",
sort_style=TableSortStyle.COMPOUND
)

Granting Privileges
You can give a user privileges to perform certain actions on a table by using the
Table.grant() method.
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:
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:
database_name = "databaseName"
username = "myuser"
table_name = "mytable"

user = User.from_user_attributes(self, "User",
username=username,
password=SecretValue.unsafe_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.
Rotating credentials
When the master password is generated and stored in AWS Secrets Manager, it can be rotated automatically:
cluster.add_rotation_single_user()

The multi user rotation scheme is also available:
user = User(self, "User",
cluster=cluster,
database_name="databaseName"
)
cluster.add_rotation_multi_user("MultiUserRotation",
secret=user.secret
)