Create your first Lambda function - AWS Lambda

Create your first Lambda function

To get started with Lambda, use the Lambda console to create a function. In a few minutes, you can create and deploy a function and test it in the console.

As you carry out the tutorial, you'll learn some fundamental Lambda concepts, like how to pass arguments to your function using the Lambda event object. You'll also learn how to return log outputs from your function, and how to view your function's invocation logs in CloudWatch Logs.

To keep things simple, you create your function using either the Python or Node.js runtime. With these interpreted languages, you can edit function code directly in the console's built-in code editor. With compiled languages like Java and C#, you need to create a deployment package on your local build machine and upload it to Lambda. To learn about deploying functions to Lambda using other runtimes, see the links in the Additional resources and next steps section.

Tip

To learn how to build serverless solutions, check out the Serverless Developer Guide.

Prerequisites

If you do not have an AWS account, complete the following steps to create one.

To sign up for an AWS account
  1. Open https://portal.aws.amazon.com/billing/signup.

  2. Follow the online instructions.

    Part of the sign-up procedure involves receiving a phone call and entering a verification code on the phone keypad.

    When you sign up for an AWS account, an AWS account root user is created. The root user has access to all AWS services and resources in the account. As a security best practice, assign administrative access to a user, and use only the root user to perform tasks that require root user access.

AWS sends you a confirmation email after the sign-up process is complete. At any time, you can view your current account activity and manage your account by going to https://aws.amazon.com/ and choosing My Account.

After you sign up for an AWS account, secure your AWS account root user, enable AWS IAM Identity Center, and create an administrative user so that you don't use the root user for everyday tasks.

Secure your AWS account root user
  1. Sign in to the AWS Management Console as the account owner by choosing Root user and entering your AWS account email address. On the next page, enter your password.

    For help signing in by using root user, see Signing in as the root user in the AWS Sign-In User Guide.

  2. Turn on multi-factor authentication (MFA) for your root user.

    For instructions, see Enable a virtual MFA device for your AWS account root user (console) in the IAM User Guide.

Create a user with administrative access
  1. Enable IAM Identity Center.

    For instructions, see Enabling AWS IAM Identity Center in the AWS IAM Identity Center User Guide.

  2. In IAM Identity Center, grant administrative access to a user.

    For a tutorial about using the IAM Identity Center directory as your identity source, see Configure user access with the default IAM Identity Center directory in the AWS IAM Identity Center User Guide.

Sign in as the user with administrative access
  • To sign in with your IAM Identity Center user, use the sign-in URL that was sent to your email address when you created the IAM Identity Center user.

    For help signing in using an IAM Identity Center user, see Signing in to the AWS access portal in the AWS Sign-In User Guide.

Assign access to additional users
  1. In IAM Identity Center, create a permission set that follows the best practice of applying least-privilege permissions.

    For instructions, see Create a permission set in the AWS IAM Identity Center User Guide.

  2. Assign users to a group, and then assign single sign-on access to the group.

    For instructions, see Add groups in the AWS IAM Identity Center User Guide.

Create a Lambda function with the console

In this example, your function takes a JSON object containing two integer values labeled "length" and "width". The function multiplies these values to calculate an area and returns this as a JSON string.

Your function also prints the calculated area, along with the name of its CloudWatch log group. Later in the tutorial, you’ll learn to use CloudWatch Logs to view records of your functions’ invocation.

To create your function, you first use the console to create a basic Hello world function. In the following step, you then add your own function code.

To create a Hello world Lambda function with the console
  1. Open the Functions page of the Lambda console.

  2. Choose Create function.

  3. Select Author from scratch.

  4. In the Basic information pane, for Function name enter myLambdaFunction.

  5. For Runtime, choose either Node.js 20.x or Python 3.12

  6. Leave architecture set to x86_64 and choose Create function.

Lambda creates a function that returns the message Hello from Lambda! Lambda also creates an execution role for your function. An execution role is an AWS Identity and Access Management (IAM) role that grants a Lambda function permission to access AWS services and resources. For your function, the role that Lambda creates grants basic permissions to write to CloudWatch Logs.

You now use the console's built-in code editor to replace the Hello world code that Lambda created with your own function code.

Node.js
To modify the code in the console
  1. Choose the Code tab.

    In the console's built-in code editor, you should see the function code that Lambda created. If you don't see the index.mjs tab in the code editor, select index.mjs in the file explorer as shown on the following diagram.

    Diagram showing the console code editor and the index.mjs file in the file explorer
  2. Paste the following code into the index.mjs tab, replacing the code that Lambda created.

    export const handler = async (event, context) => { const length = event.length; const width = event.width; let area = calculateArea(length, width); console.log(`The area is ${area}`); console.log('CloudWatch log group: ', context.logGroupName); let data = { "area": area, }; return JSON.stringify(data); function calculateArea(length, width) { return length * width; } };
  3. Select Deploy to update your function's code. When Lambda has deployed the changes, the console displays a banner letting you know that it's successfully updated your function.

Understanding your function code

Before you move to the next step, let's take a moment to look at the function code and understand some key Lambda concepts.

  • The Lambda handler:

    Your Lambda function contains a Node.js function named handler. A Lambda function in Node.js can contain more than one Node.js function, but the handler function is always the entry point to your code. When your function is invoked, Lambda runs this method.

    When you created your Hello world function using the console, Lambda automatically set the name of the handler method for your function to handler. Be sure not to edit the name of this Node.js function. If you do, Lambda won’t be able to run your code when you invoke your function.

    To learn more about the Lambda handler in Node.js, see Define Lambda function handler in Node.js.

  • The Lambda event object:

    The function handler takes two arguments, event and context. An event in Lambda is a JSON formatted document that contains data for your function to process.

    If your function is invoked by another AWS service, the event object contains information about the event that caused the invocation. For example, if an Amazon Simple Storage Service (Amazon S3) bucket invokes your function when an object is uploaded, the event will contain the name of the Amazon S3 bucket and the object key.

    In this example, you’ll create an event in the console by entering a JSON formatted document with two key-value pairs.

  • The Lambda context object:

    The second argument your function takes is context. Lambda passes the context object to your function automatically. The context object contains information about the function invocation and execution environment.

    You can use the context object to output information about your function's invocation for monitoring purposes. In this example, your function uses the logGroupName parameter to output the name of its CloudWatch log group.

    To learn more about the Lambda context object in Node.js, see Using the Lambda context object to retrieve Node.js function information.

  • Logging in Lambda:

    With Node.js, you can use console methods like console.log and console.error to send information to your function's log. The example code uses console.log statements to output the calculated area and the name of the function's CloudWatch Logs group. You can also use any logging library that writes to stdout or stderr.

    To learn more, see Log and monitor Node.js Lambda functions. To learn about logging in other runtimes, see the 'Building with' pages for the runtimes you're interested in.

Python
To modify the code in the console
  1. Choose the Code tab.

    In the console's built-in code editor, you should see the function code that Lambda created. If you don't see the lambda_function.py tab in the code editor, select lambda_function.py in the file explorer as shown on the following diagram.

    Diagram showing the console code editor and the lambda_function.py file in the file explorer
  2. Paste the following code into the lambda_function.py tab, replacing the code that Lambda created.

    import json import logging logger = logging.getLogger() logger.setLevel(logging.INFO) def lambda_handler(event, context): # Get the length and width parameters from the event object. The # runtime converts the event object to a Python dictionary length = event['length'] width = event['width'] area = calculate_area(length, width) print(f"The area is {area}") logger.info(f"CloudWatch logs group: {context.log_group_name}") # return the calculated area as a JSON string data = {"area": area} return json.dumps(data) def calculate_area(length, width): return length*width
  3. Select Deploy to update your function's code. When Lambda has deployed the changes, the console displays a banner letting you know that it's successfully updated your function.

Understanding your function code

Before you move to the next step, let's take a moment to look at the function code and understand some key Lambda concepts.

  • The Lambda handler:

    Your Lambda function contains a Python function named lambda_handler. A Lambda function in Python can contain more than one Python function, but the handler function is always the entry point to your code. When your function is invoked, Lambda runs this method.

    When you created your Hello world function using the console, Lambda automatically set the name of the handler method for your function to lambda_handler. Be sure not to edit the name of this Python function. If you do, Lambda won’t be able to run your code when you invoke your function.

    To learn more about the Lambda handler in Python, see Define Lambda function handler in Python.

  • The Lambda event object:

    The function lambda_handler takes two arguments, event and context. An event in Lambda is a JSON formatted document that contains data for your function to process.

    If your function is invoked by another AWS service, the event object contains information about the event that caused the invocation. For example, if an Amazon Simple Storage Service (Amazon S3) bucket invokes your function when an object is uploaded, the event will contain the name of the Amazon S3 bucket and the object key.

    In this example, you’ll create an event in the console by entering a JSON formatted document with two key-value pairs.

  • The Lambda context object:

    The second argument your function takes is context. Lambda passes the context object to your function automatically. The context object contains information about the function invocation and execution environment.

    You can use the context object to output information about your function's invocation for monitoring purposes. In this example, your function uses the log_group_name parameter to output the name of its CloudWatch log group.

    To learn more about the Lambda context object in Python, see Using the Lambda context object to retrieve Python function information.

  • Logging in Lambda:

    With Python, you can use either a print statement or a Python logging library to send information to your function's log. To illustrate the difference in what's captured, the example code uses both methods. In a production application, we recommend that you use a logging library.

    To learn more, see Log and monitor Python Lambda functions. To learn about logging in other runtimes, see the 'Building with' pages for the runtimes you're interested in.

Invoke the Lambda function using the console

To invoke your function using the Lambda console, you first create a test event to send to your function. The event is a JSON formatted document containing two key-value pairs with the keys "length" and "width".

To create the test event
  1. In the Code source pane, choose Test.

  2. Select Create new event.

  3. For Event name enter myTestEvent.

  4. In the Event JSON panel, replace the default values by pasting in the following:

    { "length": 6, "width": 7 }
  5. Choose Save.

You now test your function and use the Lambda console and CloudWatch Logs to view records of your function’s invocation.

To test your function and view invocation records in the console
  • In the Code source pane, choose Test. When your function finishes running, you’ll see the response and function logs displayed in the Execution results tab. You should see results similar to the following.

    Node.js
    Test Event Name myTestEvent Response "{\"area\":42}" Function Logs START RequestId: 5c012b0a-18f7-4805-b2f6-40912935034a Version: $LATEST 2023-08-31T23:39:45.313Z 5c012b0a-18f7-4805-b2f6-40912935034a INFO The area is 42 2023-08-31T23:39:45.331Z 5c012b0a-18f7-4805-b2f6-40912935034a INFO CloudWatch log group: /aws/lambda/myLambdaFunction END RequestId: 5c012b0a-18f7-4805-b2f6-40912935034a REPORT RequestId: 5c012b0a-18f7-4805-b2f6-40912935034a Duration: 20.67 ms Billed Duration: 21 ms Memory Size: 128 MB Max Memory Used: 66 MB Init Duration: 163.87 ms Request ID 5c012b0a-18f7-4805-b2f6-40912935034a
    Python
    Test Event Name myTestEvent Response "{\"area\": 42}" Function Logs START RequestId: 2d0b1579-46fb-4bf7-a6e1-8e08840eae5b Version: $LATEST The area is 42 [INFO] 2023-08-31T23:43:26.428Z 2d0b1579-46fb-4bf7-a6e1-8e08840eae5b CloudWatch logs group: /aws/lambda/myLambdaFunction END RequestId: 2d0b1579-46fb-4bf7-a6e1-8e08840eae5b REPORT RequestId: 2d0b1579-46fb-4bf7-a6e1-8e08840eae5b Duration: 1.42 ms Billed Duration: 2 ms Memory Size: 128 MB Max Memory Used: 39 MB Init Duration: 123.74 ms Request ID 2d0b1579-46fb-4bf7-a6e1-8e08840eae5b

In this example, you invoked your code using the console's test feature. This means that you can view your function's execution results directly in the console. When your function is invoked outside the console, you need to use CloudWatch Logs.

To view your function's invocation records in CloudWatch Logs
  1. Open the Log groups page of the CloudWatch console.

  2. Choose the log group for your function (/aws/lambda/myLambdaFunction). This is the log group name that your function printed to the console.

  3. In the Log streams tab, choose the log stream for your function's invocation.

    You should see output similar to the following:

    Node.js
    INIT_START Runtime Version: nodejs:20.v13 Runtime Version ARN: arn:aws:lambda:us-west-2::runtime:e3aaabf6b92ef8755eaae2f4bfdcb7eb8c4536a5e044900570a42bdba7b869d9 START RequestId: aba6c0fc-cf99-49d7-a77d-26d805dacd20 Version: $LATEST 2023-08-23T22:04:15.809Z 5c012b0a-18f7-4805-b2f6-40912935034a INFO The area is 42 2023-08-23T22:04:15.810Z aba6c0fc-cf99-49d7-a77d-26d805dacd20 INFO CloudWatch log group: /aws/lambda/myLambdaFunction END RequestId: aba6c0fc-cf99-49d7-a77d-26d805dacd20 REPORT RequestId: aba6c0fc-cf99-49d7-a77d-26d805dacd20 Duration: 17.77 ms Billed Duration: 18 ms Memory Size: 128 MB Max Memory Used: 67 MB Init Duration: 178.85 ms
    Python
    INIT_START Runtime Version: python:3.12.v16 Runtime Version ARN: arn:aws:lambda:us-west-2::runtime:ca202755c87b9ec2b58856efb7374b4f7b655a0ea3deb1d5acc9aee9e297b072 START RequestId: 9d4096ee-acb3-4c25-be10-8a210f0a9d8e Version: $LATEST The area is 42 [INFO] 2023-09-01T00:05:22.464Z 9315ab6b-354a-486e-884a-2fb2972b7d84 CloudWatch logs group: /aws/lambda/myLambdaFunction END RequestId: 9d4096ee-acb3-4c25-be10-8a210f0a9d8e REPORT RequestId: 9d4096ee-acb3-4c25-be10-8a210f0a9d8e Duration: 1.15 ms Billed Duration: 2 ms Memory Size: 128 MB Max Memory Used: 40 MB

Clean up

When you're finished working with the example function, delete it. You can also delete the log group that stores the function's logs, and the execution role that the console created.

To delete a Lambda function
  1. Open the Functions page of the Lambda console.

  2. Choose a function.

  3. Choose Actions, Delete.

  4. In the Delete function dialog box, enter delete, and then choose Delete.

To delete the log group
  1. Open the Log groups page of the CloudWatch console.

  2. Select the function's log group (/aws/lambda/my-function).

  3. Choose Actions, Delete log group(s).

  4. In the Delete log group(s) dialog box, choose Delete.

To delete the execution role
  1. Open the Roles page of the AWS Identity and Access Management (IAM) console.

  2. Select the function's execution role (for example, myLambdaFunction-role-31exxmpl).

  3. Choose Delete.

  4. In the Delete role dialog box, enter the role name and then choose Delete.

You can automate the creation and cleanup of functions, log groups, and roles with AWS CloudFormation and the AWS Command Line Interface (AWS CLI).

Additional resources and next steps

Now you’ve created and tested a simple Lambda function using the console, take these next steps: