Amazon Relational Database Service
User Guide (API Version 2014-10-31)

Invoking a Lambda Function from an Amazon Aurora DB Cluster


Integration with AWS Lambda is available for Amazon Aurora version 1.8 and later. For more information on Aurora versions, see Amazon Aurora Database Engine Updates.

You can invoke an AWS Lambda function from an Amazon Aurora DB cluster by calling the mysql.lambda_async procedure. This approach can be useful when you want to integrate your database running on Amazon Aurora with other AWS services. For example, you might want to send a notification using Amazon Simple Notification Service (Amazon SNS) whenever a row is inserted into a specific table in your database.

To invoke a Lambda function, you grant your Aurora DB cluster permission to access AWS Lambda. You grant permission by creating an IAM role with the necessary permissions, and then associating the role with your DB cluster. You must also configure your Aurora DB cluster to allow outbound connections to AWS Lambda. For details and instructions on how to permit your Aurora DB cluster to communicate with AWS Lambda on your behalf, see Authorizing Amazon Aurora to Access Other AWS Services on Your Behalf.

Working with the mysql.lambda_async Procedure to Invoke a Lambda Function

The mysql.lambda_async procedure is a built-in stored procedure that invokes a Lambda function asynchronously. To use this procedure, your database user must have execute privilege on the mysql.lambda_async stored procedure.


CALL mysql.lambda_async ( lambda_function_ARN, lambda_function_input )



The Amazon Resource Name (ARN) of the Lambda function to invoke.


The input string, in JSON format, for the invoked Lambda function.


As a best practice, we recommend that you wrap calls to the mysql.lambda_async procedure in a stored procedure that can be called from different sources such as triggers or client code. This approach can help to avoid impedance mismatch issues and make it easier to invoke Lambda functions.

Example: Invoke an AWS Lambda Function to Send Email

The following example creates a stored procedure that you can call in your database code to send an email using a Lambda function.

AWS Lambda Function

import boto3 ses = boto3.client('ses') def SES_send_email(event, context): return ses.send_email( Source=event['email_from'], Destination={ 'ToAddresses': [ event['email_to'], ] }, Message={ 'Subject': { 'Data': event['email_subject'] }, 'Body': { 'Text': { 'Data': event['email_body'] } } } )

Stored Procedure

DROP PROCEDURE IF EXISTS SES_send_email; DELIMITER ;; CREATE PROCEDURE SES_send_email(IN email_from VARCHAR(255), IN email_to VARCHAR(255), IN subject VARCHAR(255), IN body TEXT) LANGUAGE SQL BEGIN CALL mysql.lambda_async( 'arn:aws:lambda:us-west-2:123456789012:function:SES_send_email', CONCAT('{"email_to" : "', email_to, '", "email_from" : "', email_from, '", "email_subject" : "', subject, '", "email_body" : "', body, '"}') ); END ;; DELIMITER ;

Call the Stored Procedure to Invoke the AWS Lambda Function

mysql> call SES_send_email('', '', 'Email subject', 'Email content');

Example: Invoke an AWS Lambda Function to Publish an Event from a Trigger

The following example creates a stored procedure that publishes an event by using Amazon SNS. The code calls the procedure from a trigger when a row is added to a table.


Be careful when invoking an AWS Lambda function from triggers on tables that experience high write traffic. INSERT, UPDATE and DELETE triggers are activated per row. A write-heavy workload on a table with INSERT, UPDATE, or DELETE triggers results in a large number of calls to your AWS Lambda function.

Although calls to the mysql.lambda_async procedure are asynchronous, triggers are synchronous. A statement that results in a large number of trigger activations doesn't wait for the call to the AWS Lambda function to complete, but it does wait for the triggers to complete before returning control to the client.

AWS Lambda Function

import boto3 sns = boto3.client('sns') def SNS_publish_message(event, context): return sns.publish( TopicArn='arn:aws:sns:us-west-2:123456789012:Sample_Topic', Message=event['message'], Subject=event['subject'], MessageStructure='string' )

Stored Procedure

DROP PROCEDURE IF EXISTS SNS_Publish_Message; DELIMITER ;; CREATE PROCEDURE SNS_Publish_Message (IN subject VARCHAR(255), IN message TEXT) LANGUAGE SQL BEGIN CALL mysql.lambda_async('arn:aws:lambda:us-west-2:123456789012:function:SNS_publish_message', CONCAT('{ "subject" : "', subject, '", "message" : "', message, '" }') ); END ;; DELIMITER ;


CREATE TABLE `Customer_Feedback` ( `id` int(11) NOT NULL AUTO_INCREMENT, `customer_name` varchar(255) NOT NULL, `customer_feedback` varchar(1024) NOT NULL, PRIMARY KEY (`id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8;


DELIMITER ;; CREATE TRIGGER TR_Customer_Feedback_AI AFTER INSERT ON Customer_Feedback FOR EACH ROW BEGIN SELECT CONCAT('New customer feedback from ', NEW.customer_name), NEW.customer_feedback INTO @subject, @feedback; CALL SNS_Publish_Message(@subject, @feedback); END ;; DELIMITER ;

Insert a Row into the Table to Trigger the Notification

mysql> insert into Customer_Feedback (customer_name, customer_feedback) VALUES ('Sample Customer', 'Good job guys!');

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