How to Build a Serverless Application with AWS Lambda

Are you tired of managing your own server infrastructure? Do you want to focus more on writing code and delivering value to your users? Then, building a serverless application with AWS Lambda could be the right solution for you!

In this article, we'll explore the key concepts behind serverless computing, how AWS Lambda fits into this model and how to build a serverless application using AWS Lambda, Amazon API Gateway and Amazon DynamoDB. So, get excited and let's dive in!

What is Serverless Computing?

Serverless computing is an architectural approach that allows developers to write and deploy code without having to worry about the underlying server and infrastructure management. In a serverless architecture, the cloud provider abstracts away the server and provides an environment to execute the code in response to events.

This approach has many benefits, including reduced operational costs, fewer DevOps responsibilities and faster time-to-market. Instead of provisioning, configuring and maintaining servers, you can focus on writing code that responds to events like user actions or data changes.

AWS Lambda - The Serverless Compute Service

AWS Lambda is a serverless compute service provided by Amazon Web Services (AWS). It allows developers to run code in a scalable and cost-effective way by executing code in response to events. With Lambda, you only pay for the compute time consumed by your code.

Lambda supports several programming languages, including Node.js, Python, Java, C# and Go. This makes it easy for developers to use their preferred language to write serverless applications.

Lambda can be used for a variety of use cases, such as processing data streams, running background jobs, building APIs or handling webhooks. It can also be integrated with other AWS services, like Amazon S3 or Amazon DynamoDB, to build powerful serverless applications.

Building a Serverless Application with AWS Lambda

In this tutorial, we'll build a simple serverless application using AWS Lambda, Amazon API Gateway and Amazon DynamoDB. The application will allow users to create and retrieve recipes. We'll use Node.js as the programming language for this example.

Prerequisites

Before we get started, make sure you have the following prerequisites installed:

• Node.js and npm
• AWS CLI
• Git

Step 1 - Set up the Environment

We'll start by setting up the environment for our serverless application. First, create a new directory for the project and navigate into it:

mkdir my-serverless-app
cd my-serverless-app

Next, initialize a new Node.js project:

npm init -y

This command creates a new package.json file that specifies the dependencies and scripts for our project.

Step 2 - Install Dependencies

Our serverless application will use several dependencies, including the aws-sdk, which provides the SDK for interacting with AWS services, and the serverless-http, which allows us to wrap our Lambda functions as an HTTP server.

Run the following command to install the dependencies:

npm install --save aws-sdk serverless-http

Step 3 - Set up Amazon DynamoDB

Our serverless application will use Amazon DynamoDB as the database to store the recipes. We'll start by creating a new table for the recipes using the AWS CLI.

Open a terminal and run the following command to create a new table named Recipes:

aws dynamodb create-table \
    --table-name Recipes \
    --attribute-definitions AttributeName=id,AttributeType=S \
    --key-schema AttributeName=id,KeyType=HASH \
    --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5

This command creates a new table with a String type key named id. The table has a provisioned throughput of 5 reads and 5 writes per second.

Step 4 - Write the Lambda Functions

Next, we'll write the Lambda functions that will handle the requests to create and retrieve recipes. Create a new file named index.js in the root directory of the project and add the following code:

const AWS = require('aws-sdk');
const uuid = require('uuid/v4');
const dynamoDb = new AWS.DynamoDB.DocumentClient();

module.exports.create = async (event) => {
  const data = JSON.parse(event.body);

  const recipe = {
    id: uuid(),
    name: data.name,
    instructions: data.instructions,
  };

  await dynamoDb.put({
    TableName: 'Recipes',
    Item: recipe,
  }).promise();

  return {
    statusCode: 201,
    body: JSON.stringify(recipe),
  };
};

module.exports.list = async (event) => {
  const result = await dynamoDb.scan({
    TableName: 'Recipes',
  }).promise();

  return {
    statusCode: 200,
    body: JSON.stringify(result.Items),
  };
};

This code defines two Lambda functions, create and list, that handle the creation and retrieval of recipes. The create function reads the request body, generates a new id for the recipe, stores it in DynamoDB and returns the created recipe as the response.

The list function retrieves all the recipes from DynamoDB and returns them as the response.

Note that we're using the aws-sdk to interact with the DynamoDB service, and the uuid library to generate unique ids for the recipes.

Step 5 - Create the Serverless Configuration

Now that we have the Lambda functions defined, we need to configure the serverless application to deploy them. We'll use the Serverless Framework to simplify the deployment process.

Install the Serverless Framework globally using npm:

npm install -g serverless

Next, create a new file named serverless.yml in the root directory of the project, and add the following code:

service: my-serverless-app

provider:
  name: aws
  runtime: nodejs12.x
  memorySize: 128
  timeout: 10
  region: us-east-1

functions:
  create:
    handler: index.create
    events:
      - http:
          path: /recipes
          method: post

  list:
    handler: index.list
    events:
      - http:
          path: /recipes
          method: get

This configuration file defines the my-serverless-app service, using the AWS provider with Node.js 12.x as the runtime. We've also set the memory size to 128MB and the timeout to 10 seconds.

Next, we define two functions, create and list, that correspond to the Lambda functions we've defined earlier. We configure the events for each function to handle HTTP requests to the /recipes endpoint with different HTTP methods.

Step 6 - Deploy the Serverless Application

With the serverless configuration in place, we're ready to deploy our serverless application. Run the following command to deploy the application to AWS:

serverless deploy

This command deploys the Lambda functions, creates an API Gateway for the HTTP endpoints and sets up the necessary resources and permissions.

Once the deployment is complete, the command will output the endpoints for the two functions. Copy the POST and GET endpoints for the create and list functions, respectively. We'll use these endpoints to test the application.

Step 7 - Test the Serverless Application

Now that our serverless application is deployed, we can test the endpoints using a tool like cURL or Postman. Open a terminal and run the following command to create a new recipe:

curl -X POST -H "Content-Type: application/json" -d '{"name": "Pasta Carbonara", "instructions": "1. Cook the pasta in a large pot of boiling salted water. Drain well. 2. While the pasta cooks, sauté the pancetta and garlic in the olive oil in a large skillet over medium heat until crisp, about 8 minutes. 3. Whisk the eggs and cream in a bowl to blend. 4. Add the pasta to the skillet and toss to coat. Remove skillet from heat; add egg mixture and toss until the sauce coats the pasta thickly, about 1 minute. 5. Add cheese and toss again. Season with salt and pepper. Enjoy!"}' https://<api-gateway-id>.execute-api.us-east-1.amazonaws.com/dev/recipes

This command sends a POST request to the create endpoint with the recipe data in the request body. The response should be the created recipe, including the generated id.

You can also retrieve the list of recipes by running the following command:

curl https://<api-gateway-id>.execute-api.us-east-1.amazonaws.com/dev/recipes

This command sends a GET request to the list endpoint and retrieves all the recipes stored in DynamoDB.

Conclusion

Congratulations! You've built a serverless application using AWS Lambda, Amazon API Gateway and Amazon DynamoDB. You've learned the key concepts behind serverless computing, how AWS Lambda fits into this model and how to build a serverless application using Lambda.

Serverless computing is a powerful approach that enables developers to focus on writing code and delivering value to their users. AWS Lambda provides a flexible and cost-effective platform to build serverless applications that scale with your business needs.

Next, you can explore the Serverless Framework further and learn how to automate the deployment process using CI/CD pipelines. Happy serverless computing!

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