In this module you'll use AWS Lambda and Amazon DynamoDB to build a backend process for handling requests for your web application. The browser application that you deployed in the first module allows users to request that a unicorn be sent to a location of their choice. In order to fulfill those requests, the JavaScript running in the browser will need to invoke a service running in the cloud.

Serverless_Web_App_LP_assets-04

You'll implement a Lambda function that will be invoked each time a user requests a unicorn. The function will select a unicorn from the fleet, record the request in a DynamoDB table and then respond to the front-end application with details about the unicorn being dispatched.

The function is invoked from the browser using Amazon API Gateway. You'll implement that connection in the next module. For this module you'll just test your function in isolation.

Time to Complete Module: 30 Minutes

Services used: AWS Lambda, Amazon DynamoDB


Follow the step-by-step instructions below to create your serverless backend process. Click on each step number to expand the section.

  • Step 1. Create an Amazon DynamoDB Table

    Use the Amazon DynamoDB console to create a new DynamoDB table. Call your table Rides and give it a partition key called RideId with type String. The table name and partition key are case sensitive. Make sure you use the exact IDs provided. Use the defaults for all other settings.

    After you've created the table, note the ARN for use in the next step.


    1. From the AWS Management Console, choose Services then select DynamoDB under Databases.

    2. Choose Create table.

    3. Enter Rides for the Table name. This field is case sensitive.

    4. Enter RideId for the Partition key and select String for the key type. This field is case sensitive.

    5. Check the Use default settings box and choose Create.

    6. Scroll to the bottom of the Overview section of your new table and note the ARN. You will use this in the next section.

  • Step 2. Create an IAM Role for Your Lambda function

    Every Lambda function has an IAM role associated with it. This role defines what other AWS services the function is allowed to interact with. For the purposes of this workshop, you'll need to create an IAM role that grants your Lambda function permission to write logs to Amazon CloudWatch Logs and access to write items to your DynamoDB table.

    Use the IAM console to create a new role. Name it WildRydesLambda and select AWS Lambda for the role type. You'll need to attach policies that grant your function permissions to write to Amazon CloudWatch Logs and put items to your DynamoDB table.

    Attach the managed policy called AWSLambdaBasicExecutionRole to this role to grant the necessary CloudWatch Logs permissions. Also, create a custom inline policy for your role that allows the ddb:PutItem action for the table you created in the previous section.


    1. From the AWS Management Console, click on Services and then select IAM in the Security, Identity & Compliance section.

    2. Select Roles in the left navigation bar and then choose Create New Role.

    3. Select AWS Lambda for the role type.

      Note: Selecting a role type automatically creates a trust policy for your role that allows AWS services to assume this role on your behalf. If you were creating this role using the CLI, AWS CloudFormation or another mechanism, you would specify a trust policy directly.

    4. Begin typing AWSLambdaBasicExecutionRole in the Filter text box and check the box next to that role.

    5. Choose Next Step.

    6. Enter WildRydesLambda for the Role Name.

    7. Choose Create Role.

    8. Type WildRydesLambda into the filter box on the Roles page and choose the role you just created.

    9. On the Permissions tab, expand the Inline Policies section and choose the click here link to create a new inline policy.

    10. Ensure Policy Generator is selected and choose Select.

    11. Select Amazon DynamoDB from the AWS Service dropdown.

    12. Select PutItem from the Actions list.

    13. Paste the ARN of the table you created in the previous section in the Amazon Resource Name (ARN) field.

    14. Choose Add Statement.

    15. Choose Next Step then Apply Policy.

  • Step 3. Create a Lambda Function for Handling Requests

    AWS Lambda will run your code in response to events such as an HTTP request. In this step you'll build the core function that will process API requests from the web application to dispatch a unicorn. In the next module you'll use Amazon API Gateway to create a RESTful API that will expose an HTTP endpoint that can be invoked from your users' browsers. You'll then connect the Lambda function you create in this step to that API in order to create a fully functional backend for your web application.

    Use the AWS Lambda console to create a new Lambda function called RequestUnicorn that will process the API requests. Use the provided requestUnicorn.js example implementation for your function code. Just copy and paste from that file into the AWS Lambda console's editor.

    Make sure to configure your function to use the WildRydesLambda IAM role you created in the previous section.


    1. Choose on Services then select Lambda in the Compute section.

    2. Choose Create function.

    3. Choose Author from Scratch.

    4. Enter RequestUnicorn in the Name field.

    5. Select WildRydesLambda from the Existing Role dropdown.

    6. Select Create function.

    7. Copy and paste the code from requestUnicorn.js into the code entry area.

    8. Make sure Node.js 6.10 is selected under Runtime.

    9. Leave the default of index.handler for the Handler field.

  • Step 4. Test Your Implementation

    For this module you will test the function that you built using the AWS Lambda console. In the next module you will add a REST API with API Gateway so you can invoke your function from the browser-based application that you deployed in the first module.


    1. Select the Select a test event dropdown, then Configure test event.

    2. Copy and paste the following test event into the editor:

    {
        "path": "/ride",
        "httpMethod": "POST",
        "headers": {
            "Accept": "*/*",
            "Authorization": "eyJraWQiOiJLTzRVMWZs",
            "content-type": "application/json; charset=UTF-8"
        },
        "queryStringParameters": null,
        "pathParameters": null,
        "requestContext": {
            "authorizer": {
                "claims": {
                    "cognito:username": "the_username"
                }
            }
        },
        "body": "{\"PickupLocation\":{\"Latitude\":47.6174755835663,\"Longitude\":-122.28837066650185}}"
    }
    1. Enter an Event Name, choose Create, then test.

    2. Verify that the execution succeeded and that the function result looks like the following:

    {
        "statusCode": 201,
        "body": "{\"RideId\":\"SvLnijIAtg6inAFUBRT+Fg==\",\"Unicorn\":{\"Name\":\"Rocinante\",\"Color\":\"Yellow\",\"Gender\":\"Female\"},\"Eta\":\"30 seconds\"}",
        "headers": {
            "Access-Control-Allow-Origin": "*"
        }
    }