In this example we will look at how to use the Middy validator middleware with a serverless API to validate request and response schemas.

Requirements

What is Middy

Middy is a very simple middleware engine that allows you to simplify your AWS Lambda code when using Node.js. It allows you to focus on the strict business logic of your Lambda function and then attach additional common elements like authentication, authorization, validation, serialization, etc. in a modular and reusable way by decorating the main business logic.

Create an SST app

Change indicator Let’s start by creating an SST app.

$ npx create-sst@latest --template=base/example middy-validator
$ cd middy-validator
$ npm install

By default, our app will be deployed to the us-east-1 AWS region. This can be changed in the sst.config.ts in your project root.

import { SSTConfig } from "sst";

export default {
  config(_input) {
    return {
      name: "middy-validator",
      region: "us-east-1",
    };
  },
} satisfies SSTConfig;

Project layout

An SST app is made up of a couple of parts.

  1. stacks/ — App Infrastructure

    The code that describes the infrastructure of your serverless app is placed in the stacks/ directory of your project. SST uses AWS CDK, to create the infrastructure.

  2. packages/functions/ — App Code

    The code that’s run when your API is invoked is placed in the packages/functions/ directory of your project.

Create our infrastructure

Our app is made up of a simple API. The API will read two variables from the request and return a greeting message as a response.

Creating our API

Let’s start by adding the API.

Change indicator Replace the stacks/ExampleStack.ts with the following.

import { Api, StackContext } from "sst/constructs";

export function ExampleStack({ stack }: StackContext) {
  // Create a HTTP API
  const api = new Api(stack, "Api", {
    routes: {
      "POST /": "packages/functions/src/lambda.handler",
    },
  });

  // Show the endpoint in the output
  stack.addOutputs({
    ApiEndpoint: api.url,
  });
}

We are using the SST Api construct to create our API. It simply has one endpoint (the root). When we make a POST request to this endpoint the Lambda function called handler in packages/functions/src/lambda.ts will get invoked.

Change indicator Replace the code in packages/functions/src/lambda.ts with:

import { APIGatewayProxyHandlerV2 } from "aws-lambda";

export const handler: APIGatewayProxyHandlerV2 = async (event) => {
  const { fname, lname } = JSON.parse(event.body);
  return {
    statusCode: 200,
    headers: { "Content-Type": "text/plain" },
    body: `Hello, ${fname}-${lname}.`,
  };
};

We are reading two variables fname and lname from the event body and returning a simple greeting message.

Let’s test what we have so far.

Starting your dev environment

Change indicator SST features a Live Lambda Development environment that allows you to work on your serverless apps live.

$ npm run dev

The first time you run this command it’ll take a couple of minutes to deploy your app and a debug stack to power the Live Lambda Development environment.

===============
 Deploying app
===============

Preparing your SST app
Transpiling source
Linting source
Deploying stacks
dev-middy-validator-ExampleStack: deploying...

 ✅  dev-middy-validator-ExampleStack


Stack dev-middy-validator-ExampleStack
  Status: deployed
  Outputs:
    ApiEndpoint: https://bqoc5prkna.execute-api.us-east-1.amazonaws.com

The ApiEndpoint is the API we just created.

Let’s test our endpoint using the integrated SST Console. The SST Console is a web based dashboard to manage your SST apps Learn more about it in our docs.

Go to the API explorer and click on the POST / route. In the Headers tab set the content-type as JSON Content-type: application/json.

Console with headers

In the Body tab, enter the below JSON and click Send to send a POST request.

{
  "fname": "mani",
  "lname": "teja"
}

Request with correct schema

As you can see the endpoint is working as expected. We sent mani and teja as our fname and lname respectively and got Hello, mani-teja as the response.

Now let’s remove lname from the body and see what happens.

Request with incorrect schema

You’ll notice that the endpoint is working fine but it returned undefined for lname. Since we’d only sent the fname in the request, so it returned undefined in the place of lname.

In a production app it can be difficult to catch these issues. We’d like to explicitly throw an error when there is a missing parameter in the request body.

Setting up our Middy middleware

To fix this let’s use the Middy validator middleware to validate our API.

Change indicator Run the following in the packages/functions/ directory.

$ npm install --save @middy/core @middy/http-json-body-parser @middy/http-error-handler @middy/validator

Let’s understand what the above packages are.

package explanation
@middy/core The core package of the Middy framework.
@middy/http-json-body-parser A middleware that parses HTTP requests with a JSON body and converts the body into an object.
@middy/http-error-handler A middleware that handles uncaught errors that contain the properties statusCode (number) and message (string) and creates a proper HTTP response for them (using the message and the status code provided by the error object).
@middy/validator A middleware that validates incoming events and outgoing responses against custom schemas defined with the JSON schema syntax.

Adding request validation

Change indicator Replace packages/functions/src/lambda.ts with the following.

import middy from "@middy/core";
import validator from "@middy/validator";
import httpErrorHandler from "@middy/http-error-handler";
import jsonBodyParser from "@middy/http-json-body-parser";

const baseHandler = (event) => {
  // You don't need JSON.parse since we are using the jsonBodyParser middleware
  const { fname, lname } = event.body;
  return {
    statusCode: 200,
    headers: { "Content-Type": "text/plain" },
    body: `Hello, ${fname}-${lname}.`,
  };
};

const inputSchema = {
  type: "object",
  properties: {
    body: {
      type: "object",
      properties: {
        fname: { type: "string" },
        lname: { type: "string" },
      },
      required: ["fname", "lname"],
    },
  },
};

const handler = middy(baseHandler)
  .use(jsonBodyParser())
  .use(
    validator({
      inputSchema,
    })
  )
  .use(httpErrorHandler());

export { handler };

Here we are creating an inputSchema. We are explicitly setting that fname and lname are required.

Important: Compiling schemas on the fly will cause a 50-100ms performance hit during cold start for simple JSON Schemas. Precompiling is highly recommended. Read more about this.

Now go back to console and click the Send button again to send a new request.

Request with Middy schema request validation

Great! The server throws a Bad request error to let us know that something is wrong.

Adding response validation

While we are here, let’s add response validation as well.

Change indicator Replace packages/functions/src/lambda.ts with this:

import middy from "@middy/core";
import validator from "@middy/validator";
import httpErrorHandler from "@middy/http-error-handler";
import jsonBodyParser from "@middy/http-json-body-parser";

const baseHandler = (event) => {
  const { fname, lname } = event.body;
  return {
    statusCode: 200,
    headers: { "Content-Type": "text/plain" },
    body: `Hello, ${fname}-${lname}.`,
  };
};

const inputSchema = {
  type: "object",
  properties: {
    body: {
      type: "object",
      properties: {
        fname: { type: "string" },
        lname: { type: "string" },
      },
      required: ["fname", "lname"],
    },
  },
};

const outputSchema = {
  type: "object",
  required: ["body", "statusCode"],
  properties: {
    body: {
      type: "string",
    },
    statusCode: {
      type: "number",
    },
    headers: {
      type: "object",
    },
  },
};

const handler = middy(baseHandler)
  .use(jsonBodyParser())
  .use(
    validator({
      inputSchema,
      outputSchema,
    })
  )
  .use(httpErrorHandler());

export { handler };

We added a new outputSchema and added it to the Middy validator.

Let’s test our API again with correct schema and Middy validator.

Add lname parameter again in the Body tab and click Send.

Request with correct schema

Now the API is back working as expected.

If the schema violates the schema we set in our middleware, the API will throw an error. Let’s quickly try out the case of returning an invalid response.

Instead of returning a number for status code, we’ll return a string instead.

Change indicator Replace this line:

statusCode: 200,

With this:

statusCode: "success",

Let’s test the API again.

Request with Middy schema response validation

Great! The server now throws a 500 Internal Server Error to let us know that something is wrong.

Change indicator Let’s change the status code back.

statusCode: 200,

Deploying to prod

Change indicator To wrap things up we’ll deploy our app to prod.

$ npx sst deploy --stage prod

This allows us to separate our environments, so when we are working in dev, it doesn’t break the app for our users.

Once deployed, you should see something like this.

 ✅  prod-middy-validator-ExampleStack


Stack prod-middy-validator-ExampleStack
  Status: deployed
  Outputs:
    ApiEndpoint: https://bqoc5prkna.execute-api.us-east-1.amazonaws.com

Cleaning up

Finally, you can remove the resources created in this example using the following commands.

$ npx sst remove
$ npx sst remove --stage prod

Conclusion

And that’s it! We’ve got a completely validated serverless API. A local development environment, to test and make changes. And it’s deployed to production as well, so you can share it with your users. Check out the repo below for the code we used in this example. And leave a comment if you have any questions!