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Module 3: Serverless Service Backend

In this module you'll use AWS Lambda and Amazon DynamoDB to build a backend process for handling requests from 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.

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.

Serverless backend architecture

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.

If you want to skip ahead to the next module, you can launch the stack from module 4 (RESTful APIs).

Implementation Instructions

Each of the following sections provide an implementation overview and detailed, step-by-step instructions. The overview should provide enough context for you to complete the implementation if you're already familiar with the AWS Management Console or you want to explore the services yourself without following a walkthrough.

If you're using the latest version of the Chrome, Firefox, or Safari web browsers the step-by-step instructions won't be visible until you expand the section.

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.

Step-by-step instructions (expand for details)

  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.

    Create table screenshot

  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.

2. Create an IAM Role for Your Lambda function

Background

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.

High-Level Instructions

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.

Step-by-step instructions (expand for details)

  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 Lambda for the role type from the AWS service group, then click Next: Permissions

    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. Click Next: Review.

  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, choose the Add inline policy link in the lower right corner to create a new inline policy. Inline policies screenshot

  10. Select Choose a service.

  11. Begin typing DynamoDB into the search box labeled Find a service and select DynamoDB when it appears. Select policy service

  12. Choose Select actions.

  13. Begin typing PutItem into the search box labeled Filter actions and check the box next to PutItem when it appears.

  14. Select the Resources section.

  15. With the Specific option selected, choose the Add ARN link in the table section.

  16. Paste the ARN of the table you created in the previous section in the Specify ARN for table field, and choose Add.

  17. Choose Review Policy.

  18. Enter DynamoDBWriteAccess for the policy name and choose Create policy. Review Policy

3. Create a Lambda Function for Handling Requests

Background

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.

High-Level Instructions

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.

Step-by-step instructions (expand for details)

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

  2. Click Create function.

  3. Keep the default Author from scratch card selected.

  4. Enter RequestUnicorn in the Name field.

  5. Select Node.js 6.10 for the Runtime.

  6. Ensure Choose an existing role is selected from the Role dropdown.

  7. Select WildRydesLambda from the Existing Role dropdown. Create Lambda function screenshot

  8. Click on Create function.

  9. Scroll down to the Function code section and replace the exiting code in the index.js code editor with the contents of requestUnicorn.js. Create Lambda function screenshot

  10. Click "Save" in the upper right corner of the page.

Implementation Validation

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. From the main edit screen for your function, select Configure test event from the the Select a test event... dropdown. Configure test event

  2. Keep Create new test event selected.

  3. Enter TestRequestEvent in the Event name field

  4. 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}}"
}

    Configure test event

  5. Click Create.

  6. On the main function edit screen click Test with TestRequestEvent selected in the dropdown.

  7. Scroll to the top of the page and expand the Details section of the Execution result section.

  8. 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": "*"
    }
}

After you have successfully tested your new function using the Lambda console, you can move on to the next module, RESTful APIs.