Amazon Managed Streaming for Apache Kafka Construct Library

---

cfn-resources: Stable

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

cdk-constructs: Experimental

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 This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.


Amazon MSK is a fully managed service that makes it easy for you to build and run applications that use Apache Kafka to process streaming data.

The following example creates an MSK Cluster.

# vpc: ec2.Vpc

cluster = msk.Cluster(self, "Cluster",
    cluster_name="myCluster",
    kafka_version=msk.KafkaVersion.V2_8_1,
    vpc=vpc
)

Allowing Connections

To control who can access the Cluster, use the .connections attribute. For a list of ports used by MSK, refer to the MSK documentation.

# vpc: ec2.Vpc

cluster = msk.Cluster(self, "Cluster",
    cluster_name="myCluster",
    kafka_version=msk.KafkaVersion.V2_8_1,
    vpc=vpc
)

cluster.connections.allow_from(
    ec2.Peer.ipv4("1.2.3.4/8"),
    ec2.Port.tcp(2181))
cluster.connections.allow_from(
    ec2.Peer.ipv4("1.2.3.4/8"),
    ec2.Port.tcp(9094))

Cluster Endpoints

You can use the following attributes to get a list of the Kafka broker or ZooKeeper node endpoints

# cluster: msk.Cluster

CfnOutput(self, "BootstrapBrokers", value=cluster.bootstrap_brokers)
CfnOutput(self, "BootstrapBrokersTls", value=cluster.bootstrap_brokers_tls)
CfnOutput(self, "BootstrapBrokersSaslScram", value=cluster.bootstrap_brokers_sasl_scram)
CfnOutput(self, "ZookeeperConnection", value=cluster.zookeeper_connection_string)
CfnOutput(self, "ZookeeperConnectionTls", value=cluster.zookeeper_connection_string_tls)

Importing an existing Cluster

To import an existing MSK cluster into your CDK app use the .fromClusterArn() method.

cluster = msk.Cluster.from_cluster_arn(self, "Cluster", "arn:aws:kafka:us-west-2:1234567890:cluster/a-cluster/11111111-1111-1111-1111-111111111111-1")

Client Authentication

MSK supports the following authentication mechanisms.

Only one authentication method can be enabled.

TLS

To enable client authentication with TLS set the certificateAuthorityArns property to reference your ACM Private CA. More info on Private CAs.

import aws_cdk.aws_acmpca as acmpca

# vpc: ec2.Vpc

cluster = msk.Cluster(self, "Cluster",
    cluster_name="myCluster",
    kafka_version=msk.KafkaVersion.V2_8_1,
    vpc=vpc,
    encryption_in_transit=msk.EncryptionInTransitConfig(
        client_broker=msk.ClientBrokerEncryption.TLS
    ),
    client_authentication=msk.ClientAuthentication.tls(
        certificate_authorities=[
            acmpca.CertificateAuthority.from_certificate_authority_arn(self, "CertificateAuthority", "arn:aws:acm-pca:us-west-2:1234567890:certificate-authority/11111111-1111-1111-1111-111111111111")
        ]
    )
)

SASL/SCRAM

Enable client authentication with SASL/SCRAM:

# vpc: ec2.Vpc

cluster = msk.Cluster(self, "cluster",
    cluster_name="myCluster",
    kafka_version=msk.KafkaVersion.V2_8_1,
    vpc=vpc,
    encryption_in_transit=msk.EncryptionInTransitConfig(
        client_broker=msk.ClientBrokerEncryption.TLS
    ),
    client_authentication=msk.ClientAuthentication.sasl(
        scram=True
    )
)

SASL/IAM

Enable client authentication with IAM:

# vpc: ec2.Vpc

cluster = msk.Cluster(self, "cluster",
    cluster_name="myCluster",
    kafka_version=msk.KafkaVersion.V2_8_1,
    vpc=vpc,
    encryption_in_transit=msk.EncryptionInTransitConfig(
        client_broker=msk.ClientBrokerEncryption.TLS
    ),
    client_authentication=msk.ClientAuthentication.sasl(
        iam=True
    )
)