Using Lambda with self-managed Apache Kafka - Amazon Lambda
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Using Lambda with self-managed Apache Kafka


If you want to send data to a target other than a Lambda function or enrich the data before sending it, see Amazon EventBridge Pipes.

Lambda supports Apache Kafka as an event source. Apache Kafka is a an open-source event streaming platform that supports workloads such as data pipelines and streaming analytics.

You can use the Amazon managed Kafka service Amazon Managed Streaming for Apache Kafka (Amazon MSK), or a self-managed Kafka cluster. For details about using Lambda with Amazon MSK, see Using Lambda with Amazon MSK.

This topic describes how to use Lambda with a self-managed Kafka cluster. In Amazon terminology, a self-managed cluster includes non-Amazon hosted Kafka clusters. For example, you can host your Kafka cluster with a cloud provider such as Confluent Cloud.

Apache Kafka as an event source operates similarly to using Amazon Simple Queue Service (Amazon SQS) or Amazon Kinesis. Lambda internally polls for new messages from the event source and then synchronously invokes the target Lambda function. Lambda reads the messages in batches and provides these to your function as an event payload. The maximum batch size is configurable. (The default is 100 messages.)


Lambda event source mappings process each event at least once, and duplicate processing of records can occur. To avoid potential issues related to duplicate events, we strongly recommend that you make your function code idempotent. To learn more, see How do I make my Lambda function idempotent in the Amazon Knowledge Center.

For Kafka-based event sources, Lambda supports processing control parameters, such as batching windows and batch size. For more information, see Batching behavior.

For an example of how to use self-managed Kafka as an event source, see Using self-hosted Apache Kafka as an event source for Amazon Lambda on the Amazon Compute Blog.

Example event

Lambda sends the batch of messages in the event parameter when it invokes your Lambda function. The event payload contains an array of messages. Each array item contains details of the Kafka topic and Kafka partition identifier, together with a timestamp and a base64-encoded message.

{ "eventSource": "SelfManagedKafka", "bootstrapServers":",", "records":{ "mytopic-0":[ { "topic":"mytopic", "partition":0, "offset":15, "timestamp":1545084650987, "timestampType":"CREATE_TIME", "key":"abcDEFghiJKLmnoPQRstuVWXyz1234==", "value":"SGVsbG8sIHRoaXMgaXMgYSB0ZXN0Lg==", "headers":[ { "headerKey":[ 104, 101, 97, 100, 101, 114, 86, 97, 108, 117, 101 ] } ] } ] } }