AWS, Cloud Computing

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Trigger an AWS Lambda function from Amazon RDS for MySQL


In today’s fast-paced digital landscape, businesses rely on real-time data processing to gain actionable insights and deliver dynamic user experiences. Amazon Web Services (AWS) offers powerful tools to achieve this, including AWS Lambda and Amazon RDS for MySQL. Organizations can automate tasks and respond rapidly to database changes by integrating these services. In this comprehensive guide, we’ll explore how to trigger AWS Lambda functions directly from Amazon RDS for MySQL, enabling seamless data processing and event-driven architectures.

Understanding AWS Lambda and Amazon RDS for MySQL

AWS Lambda:

AWS Lambda is a serverless computing service that allows you to run code in response to events without provisioning or managing servers. You can execute functions written in various programming languages, including Node.js, Python, Java, and more. Lambda functions scale automatically and only incur charges when triggered, making them highly cost-effective for event-driven architectures.

Amazon RDS for MySQL:

Amazon RDS (Relational Database Service) simplifies database management by handling routine tasks such as patching, backups, and scaling. Amazon RDS for MySQL is a fully managed relational database service that provides high availability, durability, and performance for MySQL databases. It’s ideal for applications that require relational database capabilities with minimal administrative overhead.

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Why Trigger AWS Lambda Functions from Amazon RDS for MySQL?

Integrating AWS Lambda with Amazon RDS for MySQL offers several benefits:

  • Real-time Data Processing: Trigger AWS Lambda functions in response to database events, enabling real-time data processing and analytics.
  • Event-Driven Architecture: Build event-driven architectures where actions are triggered automatically based on database changes, leading to faster response times and improved efficiency.
  • Scalability and Cost Efficiency: AWS Lambda automatically scales to handle varying workloads, eliminating the need to provision and manage servers. You only pay for the compute time your functions consume, resulting in cost savings.
  • Streamlined Development: Simplify development by abstracting infrastructure management. Focus on writing business logic within AWS Lambda functions without worrying about server provisioning or maintenance.

Architecture Diagram


Steps to Trigger AWS Lambda Functions from Amazon RDS for MySQL

  1. Prepare Your AWS Lambda Function

Ensure your AWS Lambda function is designed to handle database events. Write the necessary code to process data and perform desired actions based on trigger events.


  1. Set Up AWS Database Migration Service (DMS)

AWS DMS facilitates data replication from Amazon RDS for MySQL to AWS Lambda. Configure DMS to create a replication task that streams database changes to AWS Lambda.


  1. Configure Your Database as a Source

Specify your Amazon RDS for MySQL instance as the source database in the AWS DMS console. Provide connection details and authentication credentials for accessing the database.


  1. Configure AWS Lambda as a Target

Select AWS Lambda as the target endpoint for your replication task. Define the Lambda function to which database events will be delivered.


  1. Set Up Data Mapping

Configure data mapping settings to specify which tables or data changes should trigger the AWS Lambda function. Define filters based on table names, columns, or types of database operations.


  1. Test and Monitor

Validate the replication task to ensure database changes correctly trigger the AWS Lambda function. Monitor the task’s status in the AWS DMS console for any errors or issues.


  1. Handle Errors and Scalability

Implement error handling mechanisms in your AWS Lambda function to manage failures gracefully. Consider scalability requirements and optimize your architecture for performance and cost efficiency.



Integrating AWS Lambda with Amazon RDS for MySQL empowers organizations to build responsive, event-driven applications that can process data in real-time.

Businesses can automate workflows, implement business logic, and gain actionable insights faster by triggering AWS Lambda functions directly from database events. With the scalability and cost-efficiency of serverless computing, AWS Lambda and Amazon RDS for MySQL offer a powerful combination for modern data-driven applications.

Following these steps, we can seamlessly trigger AWS Lambda functions from Amazon RDS for MySQL, unlocking the full potential of event-driven architectures and real-time data processing. Whether you’re building a scalable web application, implementing real-time analytics, or automating business workflows, this integration offers a flexible and efficient solution for your needs.

Drop a query if you have any questions regarding AWS Lambda or Amazon RDS and we will get back to you quickly.

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1. What is Amazon RDS for MySQL?

ANS: – Amazon RDS (Relational Database Service) for MySQL is a fully managed relational database service offered by AWS. It allows you to set up, operate, and scale MySQL databases in the cloud environment without managing the underlying infrastructure.

2. Why would I trigger an AWS Lambda function from Amazon RDS for MySQL?

ANS: – Triggering AWS Lambda functions from Amazon RDS for MySQL enables real-time data processing and event-driven architectures. It allows you to automate tasks, react to database changes instantly, and build responsive applications without managing servers.

3. How does AWS Database Migration Service (DMS) fit into the picture?

ANS: – AWS DMS facilitates data replication from Amazon RDS for MySQL to Lambda. It enables you to create replication tasks that stream database changes to Lambda functions, allowing you to trigger actions based on those changes.

WRITTEN BY Neetika Gupta

Neetika Gupta works as a Senior Research Associate in CloudThat has the experience to deploy multiple Data Science Projects into multiple cloud frameworks. She has deployed end-to-end AI applications for Business Requirements on Cloud frameworks like AWS, AZURE, and GCP and Deployed Scalable applications using CI/CD Pipelines.



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