ManagedKafkaEventSource

class aws_cdk.aws_lambda_event_sources.ManagedKafkaEventSource(*, cluster_arn, secret=None, topic, batch_size=None, bisect_batch_on_error=None, enabled=None, max_batching_window=None, max_record_age=None, on_failure=None, parallelization_factor=None, report_batch_item_failures=None, retry_attempts=None, starting_position, tumbling_window=None)

Bases: aws_cdk.aws_lambda_event_sources.StreamEventSource

Use a MSK cluster as a streaming source for AWS Lambda.

Example:

from aws_cdk.aws_secretsmanager import Secret
from aws_cdk.aws_lambda_event_sources import ManagedKafkaEventSource

# my_function is of type Function


# Your MSK cluster arn
cluster_arn = "arn:aws:kafka:us-east-1:0123456789019:cluster/SalesCluster/abcd1234-abcd-cafe-abab-9876543210ab-4"

# The Kafka topic you want to subscribe to
topic = "some-cool-topic"

# The secret that allows access to your MSK cluster
# You still have to make sure that it is associated with your cluster as described in the documentation
secret = Secret(self, "Secret", secret_name="AmazonMSK_KafkaSecret")
my_function.add_event_source(ManagedKafkaEventSource(
    cluster_arn=cluster_arn,
    topic=topic,
    secret=secret,
    batch_size=100,  # default
    starting_position=lambda_.StartingPosition.TRIM_HORIZON
))
Parameters
  • cluster_arn (str) – An MSK cluster construct.

  • secret (Optional[ISecret]) – The secret with the Kafka credentials, see https://docs.aws.amazon.com/msk/latest/developerguide/msk-password.html for details This field is required if your Kafka brokers are accessed over the Internet. Default: none

  • topic (str) – The Kafka topic to subscribe to.

  • batch_size (Union[int, float, None]) – The largest number of records that AWS Lambda will retrieve from your event source at the time of invoking your function. Your function receives an event with all the retrieved records. Valid Range: - Minimum value of 1 - Maximum value of: - 1000 for {@link DynamoEventSource} - 10000 for {@link KinesisEventSource} Default: 100

  • bisect_batch_on_error (Optional[bool]) – If the function returns an error, split the batch in two and retry. Default: false

  • enabled (Optional[bool]) – If the stream event source mapping should be enabled. Default: true

  • max_batching_window (Optional[Duration]) – The maximum amount of time to gather records before invoking the function. Maximum of Duration.minutes(5) Default: Duration.seconds(0)

  • max_record_age (Optional[Duration]) – The maximum age of a record that Lambda sends to a function for processing. Valid Range: - Minimum value of 60 seconds - Maximum value of 7 days Default: - the retention period configured on the stream

  • on_failure (Optional[IEventSourceDlq]) – An Amazon SQS queue or Amazon SNS topic destination for discarded records. Default: discarded records are ignored

  • parallelization_factor (Union[int, float, None]) – The number of batches to process from each shard concurrently. Valid Range: - Minimum value of 1 - Maximum value of 10 Default: 1

  • report_batch_item_failures (Optional[bool]) – Allow functions to return partially successful responses for a batch of records. Default: false

  • retry_attempts (Union[int, float, None]) – Maximum number of retry attempts Valid Range: * Minimum value of 0 * Maximum value of 10000. Default: - retry until the record expires

  • starting_position (StartingPosition) – Where to begin consuming the stream.

  • tumbling_window (Optional[Duration]) – The size of the tumbling windows to group records sent to DynamoDB or Kinesis Valid Range: 0 - 15 minutes. Default: - None

Methods

bind(target)

Called by lambda.addEventSource to allow the event source to bind to this function.

Parameters

target (IFunction) –

Return type

None

Attributes

event_source_mapping_id

The identifier for this EventSourceMapping.

Return type

str