Deploying a Serverless App with AWS Lambda, API Gateway, and DynamoDB.

Introduction.

In today’s cloud-native world, the way we design, build, and deploy applications has radically shifted. Gone are the days of provisioning physical servers or managing heavy virtual machine clusters just to run a simple API.

With the rise of serverless computing, developers can now focus purely on writing code, while the cloud provider handles everything else infrastructure provisioning, scaling, patching, and even high availability.

At the forefront of this revolution is Amazon Web Services (AWS), offering a mature and robust serverless ecosystem that empowers developers to build powerful, cost-effective applications with minimal operational overhead.

In this blog post, we’ll take a deep dive into deploying a serverless CRUD API using three essential AWS services: AWS Lambda, Amazon API Gateway, and Amazon DynamoDB. These three services form a golden trio that allows you to run code in response to HTTP requests, without ever launching or managing servers.

AWS Lambda is the compute powerhouse behind this setup. It lets you run your backend code in response to events such as HTTP requests, database changes, or messages from a queue and you only pay for the time your code runs. No idle compute time, no server maintenance, and automatic scaling are just a few of Lambda’s standout benefits.

Amazon API Gateway acts as the front door to your Lambda functions. It enables you to define RESTful or WebSocket APIs that clients can use to access your backend logic. It handles authorization, throttling, monitoring, request transformation, and more.

With just a few clicks (or a few lines of infrastructure-as-code), you can create robust APIs that scale automatically with demand.

To store and retrieve data, we’ll use Amazon DynamoDB, AWS’s fully managed NoSQL database service. It offers single-digit millisecond response times, seamless horizontal scaling, built-in high availability, and a flexible schema. It’s the perfect fit for serverless architectures where you need scalable, performant data storage without the headaches of managing traditional database servers.

By the end of this guide, you’ll have a working API that supports basic Create, Read, Update, and Delete operations on a Todos resource.

You’ll learn how to set up a DynamoDB table, write Lambda functions in Node.js or Python, connect them to an API Gateway endpoint, and deploy everything using the AWS Management Console or a framework like AWS SAM.

We’ll walk through each component, explain how it fits into the overall architecture, and provide working code you can adapt for your own projects.

Whether you’re a backend developer trying out serverless for the first time, a DevOps engineer exploring new deployment models, or a startup founder looking for a low-cost way to get your app online, this guide is for you.

You don’t need to be a cloud expert to follow along we’ll explain each step and offer helpful tips along the way. What you do need is an AWS account, a basic understanding of programming, and a willingness to learn something new.

So, let’s jump in and build a fully serverless application on AWS one that can scale to millions of users, with zero server management and near-zero cost at small scale. This is modern cloud development. This is serverless.

Architecture Overview.

When deploying a serverless application using AWS Lambda, Amazon API Gateway, and Amazon DynamoDB, you’re creating a highly scalable, cost-effective, and fully managed architecture that eliminates the need to manage servers.

The core concept revolves around handling user requests via HTTP endpoints, processing those requests through stateless compute functions, and persisting data in a NoSQL database all with automatic scaling and high availability. The architecture starts with Amazon API Gateway, which acts as the front door of your application.

It receives incoming HTTP(S) requests from clients such as browsers, mobile apps, or third-party services and securely routes them to the appropriate backend Lambda functions.

API Gateway handles request validation, throttling, authorization (via IAM roles, API keys, or Amazon Cognito), and transforms incoming data before forwarding it to AWS Lambda.

Once a request reaches a Lambda function, the serverless compute layer kicks in. Each Lambda function is triggered based on specific events in this case, API calls and contains the business logic necessary to process the request. Lambda automatically scales based on demand, running code in isolated environments and billing only for the compute time used, down to the millisecond.

After executing the logic (e.g., user registration, form submission, task management), the Lambda function interacts with Amazon DynamoDB, a fully managed NoSQL database service designed for speed and scale.

DynamoDB stores and retrieves data with single-digit millisecond latency, making it ideal for real-time applications. Whether you’re saving user data, querying items by key, or performing conditional updates, DynamoDB serves as the persistent data layer.

Thanks to its seamless integration with Lambda, there’s no need for database connection pooling or instance management.

This serverless trio API Gateway, Lambda, and DynamoDB forms a clean, decoupled architecture where each component scales independently and is managed entirely by AWS.

It supports stateless and event-driven application design, promoting high availability and fault tolerance out of the box. You can also enhance this setup with additional AWS services like Amazon Cognito for user authentication, AWS CloudWatch for logging and monitoring, AWS Step Functions for orchestration, and AWS SAM or Serverless Framework for deployment automation.

By using this architecture, developers can rapidly build applications without worrying about provisioning infrastructure, handling traffic spikes, or managing operating systems. It’s a highly effective approach for use cases like REST APIs, microservices, task trackers, IoT dashboards, or e-commerce backends. The combination of API Gateway, Lambda, and DynamoDB offers the ultimate in agility, cost-efficiency, and scalability making it a cornerstone pattern for modern cloud-native applications.

Prerequisites

• AWS Account
• Basic knowledge of JavaScript/Node.js or Python
• AWS CLI and SAM CLI installed (optional)
• IAM user with sufficient permissions

Step-by-Step Tutorial

1. Create a DynamoDB Table.

aws dynamodb create-table \
    --table-name Todos \
    --attribute-definitions AttributeName=id,AttributeType=S \
    --key-schema AttributeName=id,KeyType=HASH \
    --billing-mode PAY_PER_REQUEST

2. Write Lambda Functions

Example: createTodo.js in Node.js

const AWS = require('aws-sdk');
const { v4: uuidv4 } = require('uuid');

const dynamo = new AWS.DynamoDB.DocumentClient();

exports.handler = async (event) => {
    const data = JSON.parse(event.body);
    const id = uuidv4();

    await dynamo.put({
        TableName: 'Todos',
        Item: { id, ...data }
    }).promise();

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

Include other endpoints:

• getTodos.js
• updateTodo.js
• deleteTodo.js

3. Set Up API Gateway

• Create a REST API
• Define resources: /todos, /todos/{id}
• Link HTTP methods (GET, POST, PUT, DELETE) to the corresponding Lambda functions

Use the AWS Console or define via Swagger/OpenAPI.

4. Permissions

Attach a policy to the Lambda execution role to allow access to DynamoDB:

{
  "Effect": "Allow",
  "Action": [
    "dynamodb:PutItem",
    "dynamodb:GetItem",
    "dynamodb:Scan",
    "dynamodb:UpdateItem",
    "dynamodb:DeleteItem"
  ],
  "Resource": "arn:aws:dynamodb:*:*:table/Todos"
}

5. Deploy with AWS SAM or Serverless Framework (Optional)

If you want to use Infrastructure as Code:

• Create a template.yaml or serverless.yml file
• Package and deploy using:

sam build
sam deploy --guided

Testing the API

Use Postman, curl, or a frontend to test:

curl -X POST https://{api-id}.execute-api.{region}.amazonaws.com/prod/todos \
-H “Content-Type: application/json” \
-d ‘{“task”: “Learn Lambda”, “completed”: false}’

Cost Considerations.

One of the biggest advantages of building serverless applications on AWS is the potential for significant cost savings, especially at low to moderate traffic levels. With AWS Lambda, you’re charged only for the compute time your functions consume measured in milliseconds and the number of requests.

The first 1 million requests and 400,000 GB-seconds of compute time per month are included in the AWS Free Tier, making Lambda virtually free for most development and testing use cases. Similarly, Amazon API Gateway offers 1 million REST API calls per month for free, which is more than enough for most small applications or prototypes.

For data storage, Amazon DynamoDB has a free tier of 25 GB of storage and 200 million requests per month (with on-demand or provisioned capacity). It’s optimized for high-throughput, low-latency workloads and scales seamlessly, but costs can rise if your read/write volume grows significantly especially with on-demand mode.

Monitoring and logging through Amazon CloudWatch also incur additional charges based on data ingested and retained, so be sure to configure your log retention policies to avoid unexpected bills.

One important aspect of cost management in serverless architectures is visibility and optimization. AWS provides tools like the AWS Cost Explorer, Budgets, and Trusted Advisor to help you monitor usage and set alerts. It’s also a good idea to tag resources properly for cost tracking and apply throttling limits in API Gateway to avoid excessive traffic charges.

Serverless is cost-efficient when designed and scaled appropriately, but it’s important to keep an eye on usage patterns, especially as your user base grows. Always estimate projected traffic and test in advance. For most small to mid-size applications, especially those just starting out, running a serverless stack on AWS can cost pennies per month or even nothing at all.

Conclusion.

In this tutorial, we explored how to build and deploy a fully serverless application using AWS Lambda, API Gateway, and DynamoDB three core services that let you create scalable, secure, and cost-effective backends without managing any infrastructure.

We walked through creating a DynamoDB table, writing Lambda functions for CRUD operations, exposing them through API Gateway, and connecting all the pieces into a seamless serverless architecture.

This approach is not only ideal for developers looking to move fast and minimize operational overhead, but also for startups and teams that need to build resilient, auto-scaling systems at a fraction of the cost of traditional server-based architectures. With the AWS Free Tier and a pay-per-use model, serverless applications can start small and grow effortlessly.

By embracing serverless, you’re tapping into a modern cloud development paradigm where you can focus entirely on building features not provisioning, patching, or scaling servers.

As next steps, consider integrating user authentication with Amazon Cognito, adding request validation or throttling, or deploying your entire stack using AWS SAM or the Serverless Framework.

The tools and services are in your hands now it’s your turn to build something amazing.