Skip to main content

The CDK Construct Library for AWS::DynamoDB

Project description

Amazon DynamoDB Construct Library

---

cfn-resources: Stable

cdk-constructs: Stable


Here is a minimal deployable DynamoDB table definition:

table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING)
)

Importing existing tables

To import an existing table into your CDK application, use the Table.fromTableName, Table.fromTableArn or Table.fromTableAttributes factory method. This method accepts table name or table ARN which describes the properties of an already existing table:

# user: iam.User

table = dynamodb.Table.from_table_arn(self, "ImportedTable", "arn:aws:dynamodb:us-east-1:111111111:table/my-table")
# now you can just call methods on the table
table.grant_read_write_data(user)

If you intend to use the tableStreamArn (including indirectly, for example by creating an @aws-cdk/aws-lambda-event-source.DynamoEventSource on the imported table), you must use the Table.fromTableAttributes method and the tableStreamArn property must be populated.

Keys

When a table is defined, you must define it's schema using the partitionKey (required) and sortKey (optional) properties.

Billing Mode

DynamoDB supports two billing modes:

  • PROVISIONED - the default mode where the table and global secondary indexes have configured read and write capacity.
  • PAY_PER_REQUEST - on-demand pricing and scaling. You only pay for what you use and there is no read and write capacity for the table or its global secondary indexes.
table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    billing_mode=dynamodb.BillingMode.PAY_PER_REQUEST
)

Further reading: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode.

Table Class

DynamoDB supports two table classes:

  • STANDARD - the default mode, and is recommended for the vast majority of workloads.
  • STANDARD_INFREQUENT_ACCESS - optimized for tables where storage is the dominant cost.
table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    table_class=dynamodb.TableClass.STANDARD_INFREQUENT_ACCESS
)

Further reading: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.TableClasses.html

Configure AutoScaling for your table

You can have DynamoDB automatically raise and lower the read and write capacities of your table by setting up autoscaling. You can use this to either keep your tables at a desired utilization level, or by scaling up and down at pre-configured times of the day:

Auto-scaling is only relevant for tables with the billing mode, PROVISIONED.

read_scaling = table.auto_scale_read_capacity(min_capacity=1, max_capacity=50)

read_scaling.scale_on_utilization(
    target_utilization_percent=50
)

read_scaling.scale_on_schedule("ScaleUpInTheMorning",
    schedule=appscaling.Schedule.cron(hour="8", minute="0"),
    min_capacity=20
)

read_scaling.scale_on_schedule("ScaleDownAtNight",
    schedule=appscaling.Schedule.cron(hour="20", minute="0"),
    max_capacity=20
)

Further reading: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/AutoScaling.html https://aws.amazon.com/blogs/database/how-to-use-aws-cloudformation-to-configure-auto-scaling-for-amazon-dynamodb-tables-and-indexes/

Amazon DynamoDB Global Tables

You can create DynamoDB Global Tables by setting the replicationRegions property on a Table:

global_table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    replication_regions=["us-east-1", "us-east-2", "us-west-2"]
)

When doing so, a CloudFormation Custom Resource will be added to the stack in order to create the replica tables in the selected regions.

The default billing mode for Global Tables is PAY_PER_REQUEST. If you want to use PROVISIONED, you have to make sure write auto-scaling is enabled for that Table:

global_table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    replication_regions=["us-east-1", "us-east-2", "us-west-2"],
    billing_mode=dynamodb.BillingMode.PROVISIONED
)

global_table.auto_scale_write_capacity(
    min_capacity=1,
    max_capacity=10
).scale_on_utilization(target_utilization_percent=75)

When adding a replica region for a large table, you might want to increase the timeout for the replication operation:

global_table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    replication_regions=["us-east-1", "us-east-2", "us-west-2"],
    replication_timeout=Duration.hours(2)
)

Encryption

All user data stored in Amazon DynamoDB is fully encrypted at rest. When creating a new table, you can choose to encrypt using the following customer master keys (CMK) to encrypt your table:

  • AWS owned CMK - By default, all tables are encrypted under an AWS owned customer master key (CMK) in the DynamoDB service account (no additional charges apply).
  • AWS managed CMK - AWS KMS keys (one per region) are created in your account, managed, and used on your behalf by AWS DynamoDB (AWS KMS charges apply).
  • Customer managed CMK - You have full control over the KMS key used to encrypt the DynamoDB Table (AWS KMS charges apply).

Creating a Table encrypted with a customer managed CMK:

table = dynamodb.Table(self, "MyTable",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    encryption=dynamodb.TableEncryption.CUSTOMER_MANAGED
)

# You can access the CMK that was added to the stack on your behalf by the Table construct via:
table_encryption_key = table.encryption_key

You can also supply your own key:

import aws_cdk.aws_kms as kms


encryption_key = kms.Key(self, "Key",
    enable_key_rotation=True
)
table = dynamodb.Table(self, "MyTable",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    encryption=dynamodb.TableEncryption.CUSTOMER_MANAGED,
    encryption_key=encryption_key
)

In order to use the AWS managed CMK instead, change the code to:

table = dynamodb.Table(self, "MyTable",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    encryption=dynamodb.TableEncryption.AWS_MANAGED
)

Get schema of table or secondary indexes

To get the partition key and sort key of the table or indexes you have configured:

# table: dynamodb.Table

schema = table.schema()
partition_key = schema.partition_key
sort_key = schema.sort_key

Kinesis Stream

A Kinesis Data Stream can be configured on the DynamoDB table to capture item-level changes.

import aws_cdk.aws_kinesis as kinesis


stream = kinesis.Stream(self, "Stream")

table = dynamodb.Table(self, "Table",
    partition_key=dynamodb.Attribute(name="id", type=dynamodb.AttributeType.STRING),
    kinesis_stream=stream
)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aws-cdk.aws-dynamodb-1.198.0.tar.gz (316.0 kB view details)

Uploaded Source

Built Distribution

aws_cdk.aws_dynamodb-1.198.0-py3-none-any.whl (315.5 kB view details)

Uploaded Python 3

File details

Details for the file aws-cdk.aws-dynamodb-1.198.0.tar.gz.

File metadata

File hashes

Hashes for aws-cdk.aws-dynamodb-1.198.0.tar.gz
Algorithm Hash digest
SHA256 90849df5cf59b5d2c7ffc2678357abfbec47ca4b4737b65e49cb4976b40e956c
MD5 ed62f751fb18dd3c6a9909dd05d2ce85
BLAKE2b-256 935cd1ac5786e3a06bf2fbb0bc2db4e52e2f97c9de26a2acdf9fdf9f491eb3d3

See more details on using hashes here.

File details

Details for the file aws_cdk.aws_dynamodb-1.198.0-py3-none-any.whl.

File metadata

File hashes

Hashes for aws_cdk.aws_dynamodb-1.198.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a39a140b539e940495566efcf4e3590196a3b749075c5ba65a623b764f710582
MD5 e137bcb41f96c4d5a7e81309a15934e0
BLAKE2b-256 63884baca076512895abe5615630cc19c926d12f1afa25cb86368dc38f5354b0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page