April 15, 2024

Connecting AWS Lambda to an AWS RDS occasion means that you can construct serverless functions that may work together with relational databases, thereby enabling you to handle database operations with out provisioning or managing servers. This complete information walks you thru the method of establishing AWS Lambda to hook up with an RDS occasion and write information to tables, step-by-step.


Earlier than we dive into the steps, guarantee you might have the next conditions coated:

  1. An AWS account
  2. An present AWS RDS occasion operating
  3. Primary information of AWS companies, particularly Lambda and RDS
  4. Familiarity with SQL and the programming language you select for the Lambda operate (e.g., Python, Node.js)

Step 1: Set Up Your AWS RDS Occasion

First, guarantee your AWS RDS occasion is appropriately configured and accessible. When establishing your RDS occasion:

  • Select a publicly accessible occasion for straightforward connectivity, although for manufacturing environments, a personal occasion is really helpful for safety causes.
  • Be aware down the endpoint, port, and credentials as you may want these to attach out of your Lambda operate.

Step 2: Create an IAM Function for Lambda

AWS Lambda requires permissions to entry different AWS companies, together with RDS. You obtain this by creating an IAM position utilizing the next steps:

  1. Navigate to the IAM console in AWS.
  2. Click on on “Roles” then “Create position.”
  3. Choose “Lambda” because the use case.
  4. Connect insurance policies granting vital permissions. For RDS entry, the AmazonRDSDataFullAccess coverage could be a superb begin, however tailor the permissions to your wants for higher safety.
  5. Title your position and create it.

Step 3: Put together Your Lambda Perform

Select your most popular programming language (e.g., Python or Node.js) and put together your operate code. Beneath is an easy Python instance that connects to an RDS occasion and inserts information right into a desk:

import pymysql

def lambda_handler(occasion, context):

    connection = pymysql.join(host="your_rds_endpoint",







        with connection.cursor() as cursor:

            sql = "INSERT INTO `your_table` (`column1`, `column2`) VALUES (%s, %s)"

            cursor.execute(sql, ('data1', 'data2'))




Exchange placeholders along with your precise RDS occasion particulars and desk schema.

Step 4: Create Your Lambda Perform in AWS

  1. Go to the AWS Lambda console and click on “Create operate.”
  2. Title your operate, choose the runtime equivalent to your programming language, and select the IAM position created earlier.
  3. Paste your operate code within the inline code editor or add it as a .zip file in case your challenge is extra complicated.
  4. Alter the essential settings resembling timeout and reminiscence primarily based in your operate’s necessities.

Step 5: Alter VPC Settings for Lambda

On your Lambda operate to entry an RDS occasion not publicly accessible:

  1. In your Lambda operate’s configuration, go to the “VPC” settings.
  2. Choose the VPC the place your RDS occasion resides.
  3. Assign applicable subnets and safety teams which have entry to the RDS occasion.

Step 6: Take a look at Your Lambda Perform

  1. Configure a check occasion within the Lambda console with any vital enter your operate requires.
  2. Invoke your Lambda operate utilizing the check occasion and monitor the execution consequence and logs for any errors or confirmations of profitable execution.

Step 7: Monitoring and Logging

AWS Lambda integrates with CloudWatch, permitting you to watch executions and log outputs. Verify CloudWatch logs in the event you encounter points or have to confirm operations.

Step 8: Greatest Practices

  • Safety: At all times use setting variables to retailer delicate info like database credentials. Moreover, think about using AWS Secrets and techniques Supervisor.
  • Error dealing with: Implement strong error dealing with in your Lambda operate to handle connectivity points, timeouts, or information inconsistencies.
  • Efficiency: Optimize your Lambda operate for efficiency by adjusting reminiscence, timeout settings, and understanding the chilly begin phenomenon.
  • Connection administration: Use connection pooling or handle connections effectively to keep away from overwhelming your database with connections.

Instance: Writing Information to RDS from Lambda

Let’s contemplate a state of affairs the place you might have a customers desk in your RDS database, and also you need to insert a brand new person report:

CREATE TABLE customers (


    username VARCHAR(50),

    e-mail VARCHAR(50)


Your Lambda operate (assuming Python and PyMySQL) may appear like this:

import pymysql
import os

def lambda_handler(occasion, context):
    # Database connection parameters
    rds_host = os.environ['RDS_HOST']
    identify = os.environ['DB_USERNAME']
    password = os.environ['DB_PASSWORD']
    db_name = os.environ['DB_NAME']
        conn = pymysql.join(host=rds_host, person=identify, passwd=password, db=db_name, connect_timeout=5)
    besides pymysql.MySQLError as e:
            'statusCode': 500,
            'physique': 'Couldn't hook up with RDS'
    with conn.cursor() as cur:
        cur.execute("INSERT INTO customers (username, e-mail) VALUES (%s, %s)", ('JohnDoe', '[email protected]'))
        'statusCode': 200,
        'physique': 'Efficiently inserted information into RDS database'

Exchange customers, username, and e-mail with the precise desk and column names in your database.


By following these steps, you’ve got efficiently arrange a serverless AWS Lambda operate that connects to an AWS RDS occasion and writes information to tables. This setup empowers you to construct scalable, serverless functions that may work together with relational databases, harnessing the complete energy of AWS cloud companies.

Keep in mind, whereas this information offers a basis, all the time tailor your implementation to the precise wants and safety necessities of your utility. Comfortable coding!