Building Scalable APIs with .NET Core and AWS Lambda

Learn how to leverage AWS Lambda and .NET Core to build scalable, serverless APIs that handle high traffic and scale automatically.

Introduction

Building scalable APIs is a crucial task in modern application development. As applications grow, so does the need for APIs that can handle large amounts of traffic. Traditionally, developers have relied on server-based architectures to manage APIs. However, with the rise of serverless computing, APIs can now scale dynamically without the need for complex server management.

In this blog post, we will explore how to build scalable APIs using .NET Core and AWS Lambda. AWS Lambda is a serverless computing service that automatically manages the infrastructure required to run your code. Combined with .NET Core, this creates a powerful environment for developing scalable, highly available APIs that require minimal maintenance.

What is AWS Lambda?

AWS Lambda is a serverless compute service provided by Amazon Web Services. It enables you to run code without provisioning or managing servers. You only pay for the compute time your code consumes, making it cost-effective for building and running APIs and other serverless applications.

Lambda functions are event-driven and can be triggered by various AWS services such as API Gateway, S3, DynamoDB, and more. AWS Lambda automatically scales your application based on incoming traffic, meaning you don’t need to worry about provisioning or managing servers.

Lambda allows you to write your code in various languages, including C#, Python, JavaScript, and others. In this tutorial, we will focus on using .NET Core with AWS Lambda to build a scalable API. Let's start by setting up the necessary tools and environments.

The following diagram illustrates scalable apis with .net core and aws lambda:

Setting Up AWS Lambda for .NET Core

Before we start building our serverless API, let's set up AWS Lambda for .NET Core. The following tools are required:

• Visual Studio: A powerful IDE for .NET Core application development.
• Amazon AWS Account: You’ll need an AWS account to access Lambda services.
• AWS Toolkit for Visual Studio: A plugin that integrates AWS services into Visual Studio.
• AWS CLI: Command-line interface to interact with AWS services.

After installing Visual Studio, you can integrate the AWS Toolkit for Visual Studio to streamline the process of deploying AWS Lambda functions. Follow the official AWS documentation to install these tools.

Let’s begin by creating a new Lambda function using Visual Studio.

Creating a .NET Core Lambda Function

Now that we have the necessary tools set up, let's create our first Lambda function in .NET Core. Follow the steps below to create the function:

1. Open Visual Studio and create a new project.
2. Select "AWS Lambda Project" and choose the .NET Core template.
3. Write the Lambda function code. Below is a simple example of a Lambda function that returns a message.

public class Function
{
    public string FunctionHandler(APIGatewayProxyRequest request, ILambdaContext context)
    {
        return "Hello, this is your serverless API response!";
    }
}
            

This Lambda function will be triggered by an API Gateway request. You can expand on this function to handle various API requests such as GET, POST, PUT, DELETE, etc.

Deploying Lambda Function to AWS

After writing the Lambda function code, we can deploy it to AWS. Follow these steps:

1. Right-click on the project and select "Publish to AWS Lambda".
2. Choose the appropriate AWS region and set the execution role.
3. Deploy the function to AWS.

Once deployed, AWS Lambda will provide a URL that can be used to trigger your API. You can now connect your Lambda function to an API Gateway.

Setting Up API Gateway for Lambda

API Gateway is the service that allows you to expose your Lambda functions as HTTP endpoints. To create a REST API using AWS API Gateway, follow these steps:

1. Navigate to the AWS Management Console and open the API Gateway service.
2. Create a new REST API and define the resources (like "/users", "/products") for your API.
3. Link each resource to your Lambda function.
4. Deploy your API to a new stage and note the URL provided by API Gateway.

Once your API is set up, you can start making HTTP requests to the URL and trigger your Lambda function.

API Authentication with AWS

To secure your API, you can implement authentication using AWS services like Cognito, Lambda authorizers, or API keys. In this section, we'll cover how to secure your API using AWS Cognito for user authentication.

1. Set up a new AWS Cognito User Pool in the AWS Console.
2. Configure your API Gateway to require authentication using the Cognito User Pool.
3. Use the Cognito SDK in your client application to authenticate users and obtain tokens.

This will ensure that only authenticated users can access your API, providing a layer of security for your endpoints.

Performance Optimization for Serverless APIs

Once your serverless API is deployed, it’s crucial to optimize its performance. Serverless applications are highly scalable, but without proper optimization, you might face issues with latency or cost inefficiency. Here are a few tips to optimize your AWS Lambda functions:

• Optimize Cold Starts: Lambda functions can experience delays during cold starts. To mitigate this, ensure your function code is lightweight and minimizes dependencies.
• Use AWS API Gateway Caching: Enable caching for frequently requested data to reduce the load on your Lambda function.
• Optimize Function Memory Allocation: AWS Lambda allows you to configure the memory for your functions. Increase the memory to improve performance, but balance it with cost considerations.

By following these best practices, you can ensure that your API functions efficiently at scale while keeping costs under control.

Advanced Use Cases and Real-World Applications

In this section, we'll explore some advanced use cases for AWS Lambda and .NET Core APIs:

• Microservices Architecture: Build a serverless microservices architecture with multiple Lambda functions, each responsible for a specific business operation.
• Event-Driven APIs: Create APIs that respond to events from other AWS services, such as S3 file uploads, DynamoDB updates, or SNS messages.
• Real-Time Data Processing: Use Lambda to process real-time data from IoT devices or real-time user interactions, and send processed results to other services like S3 or DynamoDB.

These advanced use cases will help you leverage AWS Lambda to build powerful, scalable, and event-driven APIs in the cloud.

Conclusion

Building scalable and efficient APIs has never been easier with AWS Lambda and .NET Core. In this post, we have explored how to set up AWS Lambda, connect it to API Gateway, secure it with authentication, optimize its performance, and deploy it to the cloud. Whether you're building a simple API or a complex microservices architecture, AWS Lambda provides a powerful and flexible solution for your needs.

By following the steps outlined in this post, you can create highly scalable, secure, and cost-efficient APIs that can handle millions of requests without worrying about server management. Embrace serverless computing with AWS Lambda and .NET Core today!

© 2025 Sandeep Mhaske. All rights reserved.

Follow me on LinkedIn | GitHub