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Migrating an Amplify Backend on Serverless Framework - Part 3

This is Part Three of a three part series on Migrating an Amplify Backend on Serverless Framework. You can find Part One here and Part Two here.

This is the third and final part of our series where we're showing the steps needed to migrate an Amplify backend to Serverless Framework. After scaffolding the project in the first part, and setting up the GraphQL API in the second part, what now remains is setting up final touches like DynamoDB triggers and S3 buckets. Let's get to it.

DynamoDB Triggers

A DynamoDB trigger allows you to invoke a lambda every time a DynamoDB table is updated, and the lambda will receive the updated row in the input event. In our application, we will be using this to add a new notification to the NotificationQueue table every time an Item row is created that has remindAt set. For this purpose, let's create that lambda, which will be just a placeholder since we're focusing mainly on the Serverless configuration.

Copy the contents of handlers/process-queue/index.js to handlers/add-to-queue/index.js. This lambda has the following content:

'use strict';

module.exports.handler = async (event) => {
  return {
    statusCode: 200,
    body: JSON.stringify(
        message: 'Go Serverless v3.0! Your function executed successfully!',
        input: event,

Now we need to make a slight modification to our Item table resource, to add stream configuration. Having stream configured on the DynamoDB table is a prerequisite for a trigger to be invoked on row modification. The stream is configured by adding a StreamViewType property to the table configuration.

The table configuration for the Item resource now becomes:

    # ...other resources
      Type: AWS::DynamoDB::Table
          StreamViewType: NEW_AND_OLD_IMAGES
          - AttributeName: id
            KeyType: HASH
          - AttributeName: id
            AttributeType: S
          - AttributeName: listId
            AttributeType: S
          - IndexName: byList
              - AttributeName: listId
                KeyType: HASH
              ProjectionType: ALL
        BillingMode: PAY_PER_REQUEST
        TableName: ${self:provider.environment.ITEM_TABLE_NAME}

The only remaining part is to connect the lambda and stream configuration together. This is done in the functions property of the Serverless configuration:

  # ... other functions
    handler: handlers/add-to-queue/index.handler
      - stream:
          type: dynamodb
          arn: !GetAtt ItemTableResource.StreamArn

We have the standard lambda function definition as well as an events property that hooks up the lambda to the stream of the Item table. Again, we use an intrinsic function, in this case !GetAtt to fetch the ARN (Amazon Resource Name) of the stream. With this in place, lambda is now hooked to the Item data stream and will begin listening to modification events.

One such event might look like this:

  "Records": [
      "awsRegion": "us-east-1",
      "dynamodb": {
        "ApproximateCreationDateTime": 1632502576,
        "Keys": {
          "id": {
            "S": "..."
        "NewImage": {
          "__typename": {
            "S": "Item"
          "id": {
            "S": "..."
          "remindAt": {
            "S": "2021-09-24T16:56:15.182Z"
          "cognitoUserId": {
            "S": "..."
          "listId": {
            "S": "..."
          "title": {
            "S": "Some title"
          "notes": {
            "S": "Item notes"
        "SequenceNumber": "853010500000000020163575159",
        "SizeBytes": 356,
        "StreamViewType": "NEW_AND_OLD_IMAGES"
      "eventID": "...",
      "eventName": "INSERT",
      "eventSource": "aws:dynamodb",
      "eventSourceARN": "arn:aws:dynamodb:us-east-1:...",
      "eventVersion": "1.1"

Setting up S3 Buckets

In case a user of our app would like to upload an image as part of the todo item's note, we could upload that image to an S3 bucket and then serve it from there when displaying the note in the UI. For this to work, we would need to provision an S3 bucket through our Serverless configuration.

An S3 bucket is a resource, just like any other DynamoDB table in the configuration. We need to give it a name, so let's configure that in the environment first:

  # ...
    # ... other environment variables...
    S3_BUCKET_NAME: ${self:service}-${opt:stage, self:provider.stage}-images

The S3 bucket name is composed of service name and stage, suffixed by the string "-images". In our case, for dev environment, the bucket would be named amplified-todo-api-dev-images.

Now we need to configure the resources for this S3 bucket. We can append the following configuration to the end of the Resources section:

	# ...other resources
    Type: AWS::S3::Bucket
      BucketName: ${self:provider.environment.S3_BUCKET_NAME}
    Type: 'AWS::S3::BucketPolicy'
        Version: '2012-10-17'
          - Sid: PublicRead
            Effect: Allow
            Principal: '*'
              - 's3:GetObject'
            Resource: !Join ['', ['arn:aws:s3:::', !Ref ImageBucketResource, /*]]
        Ref: ImageBucketResource

In the above configuration, we create a resource for the bucket, and a policy specifying public read permissions for that resource. Note how ImageBucketPolicy is referencing ImageBucketResource. We're using intrinsic functions again to avoid hardcoding the image bucket resource name.

If we wanted to have a lambda that would upload to this S3 bucket, then we would need to add the permissions for it:

  # ...
    # ...other environment variables
    S3_BUCKET_NAME: ${self:service}-${opt:stage, self:provider.stage}-images
        - Effect: Allow
            - s3:PutObject
            - s3:GetObject
          Resource: 'arn:aws:s3:::${self:provider.environment.S3_BUCKET_NAME}/*'

Our S3 bucket is now set up.

Bonus: Lambda Bundling

The project in this state is relatively simple and should take less than a couple of minutes to deploy. With time, however, it will probably grow larger, and the lambdas may start to require some external dependencies. The deployment will become slower, and lambda deployments will contain more files than are really necessary. At that point, it will be a good idea to introduce lambda bundling.

serverless-esbuild is a plugin that utilizes esbuild to bundle and minify your lambda code. It's almost zero-config, and works out of the box without the need to install any additional plugins. With it, you can have both TypeScript and JavaScript code.

To start using it, install it first:

npm install --save-dev serverless-esbuild

Now add it to the plugins array:

  - serverless-esbuild
  - serverless-appsync-plugin

Finally, configure it to both bundle and minify your lambdas:

    bundle: true
    minify: true
    # ... appSync config

That's it. Your lambdas will now be bundled and minified on every deploy.


This is the end of our three-part series on migrating an Amplify backend to Serverless Framework. We hope you enjoyed the journey! Even if you're not migrating from Amplify, these guides should help you configure various services such as AppSync and DynamoDB in Serverless Framework. Don't forget that the entire source code for this project is up on GitHub. Should you need any help, though, with either Amplify or Serverless Framework, please do not hesitate to drop us a line!

This Dot Labs is a development consultancy that is trusted by top industry companies, including Stripe, Xero, Wikimedia, Docusign, and Twilio. This Dot takes a hands-on approach by providing tailored development strategies to help you approach your most pressing challenges with clarity and confidence. Whether it's bridging the gap between business and technology or modernizing legacy systems, you’ll find a breadth of experience and knowledge you need. Check out how This Dot Labs can empower your tech journey.

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Testing a Fastify app with the NodeJS test runner

Introduction Node.js has shipped a built-in test runner for a couple of major versions. Since its release I haven’t heard much about it so I decided to try it out on a simple Fastify API server application that I was working on. It turns out, it’s pretty good! It’s also really nice to start testing a node application without dealing with the hassle of installing some additional dependencies and managing more configurations. Since it’s got my stamp of approval, why not write a post about it? In this post, we will hit the highlights of the testing API and write some basic but real-life tests for an API server. This server will be built with Fastify, a plugin-centric API framework. They have some good documentation on testing that should make this pretty easy. We’ll also add a SQL driver for the plugin we will test. Setup Let's set up our simple API server by creating a new project, adding our dependencies, and creating some files. Ensure you’re running node v20 or greater (Test runner is a stable API as of the 20 major releases) Overview `index.js` - node entry that initializes our Fastify app and listens for incoming http requests on port 3001 `app.js` - this file exports a function that creates and returns our Fastify application instance `sql-plugin.js` - a Fastify plugin that sets up and connects to a SQL driver and makes it available on our app instance Application Code A simple first test For our first test we will just test our servers index route. If you recall from the app.js` code above, our index route returns a 501 response for “not implemented”. In this test, we're using the createApp` function to create a new instance of our Fastify app, and then using the `inject` method from the Fastify API to make a request to the `/` route. We import our test utilities directly from the node. Notice we can pass async functions to our test to use async/await. Node’s assert API has been around for a long time, this is what we are using to make our test assertions. To run this test, we can use the following command: By default the Node.js test runner uses the TAP reporter. You can configure it using other reporters or even create your own custom reporters for it to use. Testing our SQL plugin Next, let's take a look at how to test our Fastify Postgres plugin. This one is a bit more involved and gives us an opportunity to use more of the test runner features. In this example, we are using a feature called Subtests. This simply means when nested tests inside of a top-level test. In our top-level test call, we get a test parameter t` that we call methods on in our nested test structure. In this example, we use `t.beforeEach` to create a new Fastify app instance for each test, and call the `test` method to register our nested tests. Along with `beforeEach` the other methods you might expect are also available: `afterEach`, `before`, `after`. Since we don’t want to connect to our Postgres database in our tests, we are using the available Mocking API to mock out the client. This was the API that I was most excited to see included in the Node Test Runner. After the basics, you almost always need to mock some functions, methods, or libraries in your tests. After trying this feature, it works easily and as expected, I was confident that I could get pretty far testing with the new Node.js core API’s. Since my plugin only uses the end method of the Postgres driver, it’s the only method I provide a mock function for. Our second test confirms that it gets called when our Fastify server is shutting down. Additional features A lot of other features that are common in other popular testing frameworks are also available. Test styles and methods Along with our basic test` based tests we used for our Fastify plugins - `test` also includes `skip`, `todo`, and `only` methods. They are for what you would expect based on the names, skipping or only running certain tests, and work-in-progress tests. If you prefer, you also have the option of using the describe` → `it` test syntax. They both come with the same methods as `test` and I think it really comes down to a matter of personal preference. Test coverage This might be the deal breaker for some since this feature is still experimental. As popular as test coverage reporting is, I expect this API to be finalized and become stable in an upcoming version. Since this isn’t something that’s being shipped for the end user though, I say go for it. What’s the worst that could happen really? Other CLI flags —watch` - —test-name-pattern` - TypeScript support You can use a loader like you would for a regular node application to execute TypeScript files. Some popular examples are tsx` and `ts-node`. In practice, I found that this currently doesn’t work well since the test runner only looks for JS file types. After digging in I found that they added support to locate your test files via a glob string but it won’t be available until the next major version release. Conclusion The built-in test runner is a lot more comprehensive than I expected it to be. I was able to easily write some real-world tests for my application. If you don’t mind some of the features like coverage reporting being experimental, you can get pretty far without installing any additional dependencies. The biggest deal breaker on many projects at this point, in my opinion, is the lack of straightforward TypeScript support. This is the test command that I ended up with in my application: I’ll be honest, I stole this from a GitHub issue thread and I don’t know exactly how it works (but it does). If TypeScript is a requirement, maybe stick with Jest or Vitest for now 🙂...