enum MetricType

Language	Type name
.NET	`Amazon.CDK.AWS.Lambda.MetricType`
Go	`github.com/aws/aws-cdk-go/awscdk/v2/awslambda#MetricType`
Java	`software.amazon.awscdk.services.lambda.MetricType`
Python	`aws_cdk.aws_lambda.MetricType`
TypeScript (source)	`aws-cdk-lib` » `aws_lambda` » `MetricType`

Example

import * as eventsources from 'aws-cdk-lib/aws-lambda-event-sources';
import * as dynamodb from 'aws-cdk-lib/aws-dynamodb';

declare const fn: lambda.Function;
const table = new dynamodb.Table(this, 'Table', {
  partitionKey: {
    name: 'id',
    type: dynamodb.AttributeType.STRING,
  },
  stream: dynamodb.StreamViewType.NEW_IMAGE,
});

fn.addEventSource(new eventsources.DynamoEventSource(table, {
  startingPosition: lambda.StartingPosition.LATEST,
  metricsConfig: {
    metrics: [lambda.MetricType.EVENT_COUNT],
  }
}));

Members

Name	Description
EVENT_COUNT	Event Count metrics provide insights into the processing behavior of your event source mapping, including the number of events successfully processed, filtered out, or dropped.
ERROR_COUNT	Error Count metrics provide insights into invocation errors and failures in your event source mapping processing.
KAFKA_METRICS	Kafka-specific metrics provide detailed insights into Kafka consumer behavior, including lag, throughput, and partition-specific metrics.

EVENT_COUNT

Event Count metrics provide insights into the processing behavior of your event source mapping, including the number of events successfully processed, filtered out, or dropped.

These metrics help you monitor the flow and status of events through your event source mapping.

ERROR_COUNT

Error Count metrics provide insights into invocation errors and failures in your event source mapping processing.

KAFKA_METRICS

Kafka-specific metrics provide detailed insights into Kafka consumer behavior, including lag, throughput, and partition-specific metrics.

AWS CDK