I have a setup where there is a node.js application that writes to a kinesis stream using putRecords for two items. The kinesis stream feeds a Lambda function that is configured with an eventSourceMapping with a batch size of 1. However, when I debug what the Records Kinesis feeds the lambda for an invocation, I see that the lambda is processing two records. Both of these records are on the same shard and have a sequence number which is pretty close.

The interesting thing is that if I switch the node.js published to use putRecord instead of putRecords, the kinesis records have a slightly farther apart sequence number and the lambda is fed the records individually.

The java code to configure the event source mapping
```
        AWSLambdaAsync lambdaClient = AWSResourceFactory.getLambdaClient();
        CreateEventSourceMappingRequest request = new CreateEventSourceMappingRequest();
        request.setEventSourceArn(kinesisArn);
        request.setFunctionName(functionName);
        request.setEnabled(true);
        request.setStartingPosition(EventSourcePosition.TRIM_HORIZON);
        request.setBatchSize(1);
        lambdaClient.createEventSourceMapping(request);
```

The localstack lambda output that shows multiple records being read at a time:

```
{
	"Records": [{
		"eventID": "shardId-000000000000:49593014281924840790139112603493819506073986345293840386",
		"eventSourceARN": "arn:aws:kinesis:us-east-1:000000000000:stream/MyStream",
		"kinesis": {
			"partitionKey": "ed0f756b97234f4fae9e3d1a886b8fbc",
			"data": "myData1",
			"sequenceNumber": "49593014281924840790139112603493819506073986345293840386"
		}
	}, {
		"eventID": "shardId-000000000000:49593014281924840790139112603495028431893600974468546562",
		"eventSourceARN": "arn:aws:kinesis:us-east-1:000000000000:stream/MyStream",
		"kinesis": {
			"partitionKey": "abee63a9299385699d65e89a290a9065",
			"data": "myData2",
			"sequenceNumber": "49593014281924840790139112603495028431893600974468546562"
		}
	}]
}
```

mapping = {
        'UUID': str(uuid.uuid4()),
        'StateTransitionReason': 'User action',
        'LastModified': float(time.mktime(datetime.utcnow().timetuple())),
        'BatchSize': 100,
        'State': 'Enabled' if enabled is True or enabled is None else 'Disabled',
        'FunctionArn': func_arn(function_name),
        'EventSourceArn': source_arn,
        'LastProcessingResult': 'OK',
        'StartingPosition': LAMBDA_DEFAULT_STARTING_POSITION
    }
    event_source_mappings.append(mapping)
    return mapping
def update_event_source(uuid_value, function_name, enabled, batch_size):
    for m in event_source_mappings:
        if uuid_value == m['UUID']:
            if function_name:
                m['FunctionArn'] = func_arn(function_name)
            m['BatchSize'] = batch_size
            m['State'] = 'Enabled' if enabled is True else 'Disabled'
            m['LastModified'] = float(time.mktime(datetime.utcnow().timetuple()))
            return m
    return {}
def delete_event_source(uuid_value):
    for i, m in enumerate(event_source_mappings):
        if uuid_value == m['UUID']:
            return event_source_mappings.pop(i)
    return {}
def use_docker():