Working with AWS Lambda: A Beginner's Guide

April 9, 2024·4 min read
by Anthony Coffey

AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS) that allows developers to run code without provisioning or managing servers. It is an event-driven platform that executes your code in response to triggers such as HTTP requests, changes in data, or shifts in system state. In this article, we will cover the basics of working with AWS Lambda, including its key features, how to create and deploy a Lambda function, and best practices.

Key Features of AWS Lambda

  1. Serverless: AWS Lambda abstracts away the underlying infrastructure, allowing you to focus on writing code without worrying about server management.

  2. Scalability: Lambda automatically scales your application by running code in response to each trigger. Your code can be triggered thousands of times per second, and each invocation can be handled independently.

  3. Cost-Effective: With Lambda, you pay only for the compute time you consume. There is no charge when your code is not running.

  4. Event-Driven: Lambda is designed to work with AWS services and other web applications as an event-driven platform. It can respond to events from services like S3, DynamoDB, SNS, and many more.

  5. Integrated Security: Lambda integrates with AWS Identity and Access Management (IAM), allowing you to set permissions for your functions and ensuring secure access to other AWS services.

Creating and Deploying an AWS Lambda Function

Step 1: Setting Up

Before you start, make sure you have an AWS account and the AWS CLI (Command Line Interface) installed and configured on your machine.

Step 2: Creating a Lambda Function

  1. Navigate to the AWS Management Console: Log in to your AWS account and go to the AWS Lambda service page.

  2. Create a New Function: Click on the "Create function" button. You can choose to author a function from scratch, use a blueprint, or browse the AWS Serverless Application Repository.

  3. Configure the Function: Enter a name for your function, select a runtime (e.g., Node.js, Python, Java), and choose an execution role that grants the function permission to access AWS resources.

Step 3: Writing Your Function Code

Write your function code in the inline editor provided by the AWS console or upload a ZIP file containing your code and dependencies. For example, a simple Node.js function that returns a message:

exports.handler = async (event) => {
  return 'Hello from Lambda!';

Step 4: Setting Up Triggers

Configure the trigger that will invoke your Lambda function. For instance, you can set up an API Gateway trigger to create an HTTP endpoint that invokes your function when accessed.

Step 5: Deploying and Testing

Once your function is configured, click on the "Deploy" button to deploy your function. You can then test your function by configuring a test event and clicking the "Test" button.

Best Practices for Working with AWS Lambda

  1. Optimize Your Code: Write efficient code to reduce execution time and minimize costs.

  2. Use Environment Variables: Store sensitive information and configuration settings in environment variables instead of hardcoding them in your function code.

  3. Monitor Your Functions: Use AWS CloudWatch to monitor your Lambda functions' performance and set up alarms to notify you of any issues.

  4. Implement Error Handling: Ensure your function code handles errors gracefully and logs relevant information for debugging.

  5. Manage Dependencies: Keep your function's dependencies up to date and minimize the package size for faster deployment and startup times.

  6. Secure Your Functions: Follow the principle of least privilege by granting only the necessary permissions to your Lambda functions.


AWS Lambda offers a powerful and flexible platform for running serverless applications. By understanding the basics of creating, deploying, and managing Lambda functions, you can leverage this service to build scalable and cost-effective applications. As you become more familiar with Lambda, you can explore advanced features such as Layers, custom runtimes, and integration with other AWS services to further enhance your serverless applications.