Project Links

Meta

Author: Amazon Web Services

Requires Python: ~=3.7

Classifiers

Intended Audience

Developers

Operating System

OS Independent

Programming Language

JavaScript
Python :: 3 :: Only
Python :: 3.7
Python :: 3.8
Python :: 3.9
Python :: 3.10
Python :: 3.11

Typing

Typed

Development Status

7 - Inactive

License

OSI Approved

Framework

AWS CDK
AWS CDK :: 1

Amazon Kinesis 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 This package is no longer being updated, and users should migrate to AWS CDK v2.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.

Amazon Kinesis provides collection and processing of large streams of data records in real time. Kinesis data streams can be used for rapid and continuous data intake and aggregation.

Streams

Streams

Amazon Kinesis Data Streams ingests a large amount of data in real time, durably stores the data, and makes the data available for consumption.

Using the CDK, a new Kinesis stream can be created as part of the stack using the construct's constructor. You may specify the streamName to give your own identifier to the stream. If not, CloudFormation will generate a name.

kinesis.Stream(self, "MyFirstStream",
    stream_name="my-awesome-stream"
)

You can also specify properties such as shardCount to indicate how many shards the stream should choose and a retentionPeriod to specify how long the data in the shards should remain accessible. Read more at Creating and Managing Streams

kinesis.Stream(self, "MyFirstStream",
    stream_name="my-awesome-stream",
    shard_count=3,
    retention_period=Duration.hours(48)
)

Encryption

Stream encryption enables server-side encryption using an AWS KMS key for a specified stream.

Encryption is enabled by default on your stream with the master key owned by Kinesis Data Streams in regions where it is supported.

kinesis.Stream(self, "MyEncryptedStream")

You can enable encryption on your stream with a user-managed key by specifying the encryption property. A KMS key will be created for you and associated with the stream.

kinesis.Stream(self, "MyEncryptedStream",
    encryption=kinesis.StreamEncryption.KMS
)

You can also supply your own external KMS key to use for stream encryption by specifying the encryptionKey property.

key = kms.Key(self, "MyKey")

kinesis.Stream(self, "MyEncryptedStream",
    encryption=kinesis.StreamEncryption.KMS,
    encryption_key=key
)

Import

Any Kinesis stream that has been created outside the stack can be imported into your CDK app.

Streams can be imported by their ARN via the Stream.fromStreamArn() API

imported_stream = kinesis.Stream.from_stream_arn(self, "ImportedStream", "arn:aws:kinesis:us-east-2:123456789012:stream/f3j09j2230j")

Encrypted Streams can also be imported by their attributes via the Stream.fromStreamAttributes() API

imported_stream = kinesis.Stream.from_stream_attributes(self, "ImportedEncryptedStream",
    stream_arn="arn:aws:kinesis:us-east-2:123456789012:stream/f3j09j2230j",
    encryption_key=kms.Key.from_key_arn(self, "key", "arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012")
)

Permission Grants

IAM roles, users or groups which need to be able to work with Amazon Kinesis streams at runtime should be granted IAM permissions.

Any object that implements the IGrantable interface (has an associated principal) can be granted permissions by calling:

grantRead(principal) - grants the principal read access
grantWrite(principal) - grants the principal write permissions to a Stream
grantReadWrite(principal) - grants principal read and write permissions

Read Permissions

Grant read access to a stream by calling the grantRead() API. If the stream has an encryption key, read permissions will also be granted to the key.

lambda_role = iam.Role(self, "Role",
    assumed_by=iam.ServicePrincipal("lambda.amazonaws.com"),
    description="Example role..."
)

stream = kinesis.Stream(self, "MyEncryptedStream",
    encryption=kinesis.StreamEncryption.KMS
)

# give lambda permissions to read stream
stream.grant_read(lambda_role)

The following read permissions are provided to a service principal by the grantRead() API:

kinesis:DescribeStreamSummary
kinesis:GetRecords
kinesis:GetShardIterator
kinesis:ListShards
kinesis:SubscribeToShard

Write Permissions

Grant write permissions to a stream is provided by calling the grantWrite() API. If the stream has an encryption key, write permissions will also be granted to the key.

lambda_role = iam.Role(self, "Role",
    assumed_by=iam.ServicePrincipal("lambda.amazonaws.com"),
    description="Example role..."
)

stream = kinesis.Stream(self, "MyEncryptedStream",
    encryption=kinesis.StreamEncryption.KMS
)

# give lambda permissions to write to stream
stream.grant_write(lambda_role)

The following write permissions are provided to a service principal by the grantWrite() API:

kinesis:ListShards
kinesis:PutRecord
kinesis:PutRecords

Custom Permissions

You can add any set of permissions to a stream by calling the grant() API.

user = iam.User(self, "MyUser")

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

# give my user permissions to list shards
stream.grant(user, "kinesis:ListShards")

Metrics

You can use common metrics from your stream to create alarms and/or dashboards. The stream.metric('MetricName') method creates a metric with the stream namespace and dimension. You can also use pre-define methods like stream.metricGetRecordsSuccess(). To find out more about Kinesis metrics check Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch.

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

# Using base metric method passing the metric name
stream.metric("GetRecords.Success")

# using pre-defined metric method
stream.metric_get_records_success()

# using pre-defined and overriding the statistic
stream.metric_get_records_success(statistic="Maximum")