ASP.NET Core and Serverless Architectures: An Overview

Embracing the Future of Scalable Web Development

The combination of ASP.NET Core and serverless architectures represents a paradigm shift in how we build and deploy modern web applications. This powerful duo offers developers the ability to create highly scalable, cost-effective solutions that automatically adjust to demand while maintaining the robust features and performance that ASP.NET Core is known for.

By leveraging serverless computing with ASP.NET Core, developers can focus on writing business logic rather than managing infrastructure, resulting in faster development cycles and reduced operational overhead.

The world of web development has undergone a remarkable transformation over the past few years. Gone are the days when developers had to worry about server provisioning, capacity planning, and infrastructure management. Today, serverless architectures have emerged as a game-changing approach that allows developers to build applications without the traditional concerns of server administration.

When you combine the power of ASP.NET Core with serverless computing, you get a potent mixture that can handle everything from simple API endpoints to complex enterprise applications. This isn't just about following the latest trend – it's about fundamentally rethinking how we approach application development and deployment.

Understanding Serverless Computing

Serverless computing doesn't mean there are no servers involved. Rather, it means that as a developer, you don't need to manage, provision, or maintain servers. The cloud provider handles all the infrastructure concerns, allowing you to focus entirely on your application code.

The concept revolves around Functions as a Service (FaaS), where your code runs in stateless compute containers that are managed by the cloud provider. These containers are ephemeral and event-driven, meaning they only exist when your code is executing. This approach brings several compelling advantages that make it attractive for modern application development.

One of the most significant benefits is automatic scaling. Traditional applications require you to predict traffic patterns and provision resources accordingly. With serverless, your application automatically scales up during high traffic periods and scales down to zero when there's no demand. This elasticity ensures optimal performance while minimizing costs.

Cost efficiency is another major advantage. You only pay for the compute resources you actually use, measured in milliseconds of execution time. There are no charges for idle time, making serverless particularly cost-effective for applications with variable or unpredictable traffic patterns.

The operational overhead reduction cannot be overstated. You don't need to worry about server updates, security patches, or capacity planning. The cloud provider handles all these concerns, allowing your team to focus on delivering business value rather than managing infrastructure.

ASP.NET Core's Serverless Compatibility

ASP.NET Core was designed with modern deployment scenarios in mind, making it naturally compatible with serverless architectures. Microsoft has made significant investments in ensuring that ASP.NET Core applications can run efficiently in serverless environments.

The framework's lightweight nature and modular design make it ideal for serverless deployment. ASP.NET Core applications can start quickly, which is crucial in serverless environments where cold starts can impact performance. The framework's dependency injection system and middleware pipeline work seamlessly in serverless contexts.

Microsoft has also provided specific tooling and libraries to support serverless deployment. The Microsoft.AspNetCore.Hosting.Abstractions package includes abstractions that make it easier to host ASP.NET Core applications in various environments, including serverless platforms.

The framework's support for minimal APIs, introduced in .NET 6, further enhances its serverless capabilities. These lightweight APIs are perfect for serverless functions, allowing you to create HTTP endpoints with minimal code and overhead.

Here's a simple example of a minimal API that would work perfectly in a serverless environment:

var builder = WebApplication.CreateBuilder(args);

// Add services to the container
builder.Services.AddScoped<IUserService, UserService>();

var app = builder.Build();

// Configure the HTTP request pipeline
app.MapGet("/api/users/{id}", async (int id, IUserService userService) =>
{
    var user = await userService.GetUserAsync(id);
    return user != null ? Results.Ok(user) : Results.NotFound();
});

app.MapPost("/api/users", async (CreateUserRequest request, IUserService userService) =>
{
    var user = await userService.CreateUserAsync(request);
    return Results.Created($"/api/users/{user.Id}", user);
});

app.Run();

This minimal API approach reduces startup time and memory footprint, making it ideal for serverless deployment where quick initialization is crucial.

Major Serverless Platforms for ASP.NET Core

AWS Lambda

Amazon Web Services Lambda is one of the most mature and feature-rich serverless platforms available. AWS provides excellent support for .NET applications through the AWS Lambda .NET Core Runtime, which allows you to run ASP.NET Core applications with minimal modifications.

The AWS Toolkit for Visual Studio makes it incredibly easy to deploy ASP.NET Core applications to Lambda. You can create Lambda functions directly from Visual Studio templates, and the deployment process is streamlined through the toolkit's integration.

AWS Lambda supports both function-based and web application deployments. For ASP.NET Core web applications, you can use the Amazon.Lambda.AspNetCoreServer package, which provides a Lambda entry point that hosts your ASP.NET Core application. This approach allows you to deploy entire web applications to Lambda with minimal code changes.

Here's an example of how to configure an ASP.NET Core application for AWS Lambda:

using Amazon.Lambda.AspNetCoreServer;
using Amazon.Lambda.Core;
using Amazon.Lambda.APIGatewayEvents;

[assembly: LambdaSerializer(typeof(Amazon.Lambda.Serialization.SystemTextJson.DefaultLambdaJsonSerializer))]

namespace MyServerlessApp
{
    public class LambdaEntryPoint : APIGatewayProxyFunction
    {
        protected override void Init(IWebHostBuilder builder)
        {
            builder
                .UseStartup<Startup>()
                .UseLambdaServer();
        }
    }
}

The integration with other AWS services is seamless. Your Lambda functions can easily connect to services like DynamoDB for data storage, S3 for file handling, and API Gateway for HTTP routing. This ecosystem approach makes it possible to build comprehensive serverless applications entirely within the AWS environment.

Azure Functions

Microsoft's Azure Functions provides native support for ASP.NET Core applications, making it a natural choice for .NET developers. The platform offers both in-process and isolated worker process models, giving you flexibility in how you structure your applications.

Azure Functions supports HTTP triggers that work exceptionally well with ASP.NET Core. You can use the familiar MVC pattern, dependency injection, and all the features you're accustomed to in traditional ASP.NET Core applications. The development experience is smooth, with excellent tooling support in Visual Studio and VS Code.

Here's an example of an Azure Function using ASP.NET Core:

using Microsoft.AspNetCore.Http;
using Microsoft.AspNetCore.Mvc;
using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Extensions.Http;
using Microsoft.Extensions.Logging;
using System.Threading.Tasks;

namespace MyAzureFunctions
{
    public class ProductsFunction
    {
        private readonly IProductService _productService;

        public ProductsFunction(IProductService productService)
        {
            _productService = productService;
        }

        [FunctionName("GetProducts")]
        public async Task<IActionResult> GetProducts(
            [HttpTrigger(AuthorizationLevel.Function, "get", Route = "products")] HttpRequest req,
            ILogger log)
        {
            log.LogInformation("C# HTTP trigger function processed a request.");

            var products = await _productService.GetProductsAsync();
            return new OkObjectResult(products);
        }

        [FunctionName("CreateProduct")]
        public async Task<IActionResult> CreateProduct(
            [HttpTrigger(AuthorizationLevel.Function, "post", Route = "products")] HttpRequest req,
            ILogger log)
        {
            var product = await req.ReadFromJsonAsync<Product>();
            var createdProduct = await _productService.CreateProductAsync(product);
            return new CreatedResult($"/api/products/{createdProduct.Id}", createdProduct);
        }
    }
}

The integration with Azure services is comprehensive. Your functions can connect to Azure SQL Database, Cosmos DB, Service Bus, and numerous other Azure services. The platform also provides built-in authentication and authorization capabilities through Azure Active Directory.

One of the standout features of Azure Functions is its support for Durable Functions, which allows you to write stateful functions in a stateless compute environment. This capability is particularly useful for complex workflows and long-running processes.

Google Cloud Functions

Google Cloud Functions has been expanding its support for .NET applications, though it's newer compared to AWS Lambda and Azure Functions. The platform supports .NET through container-based deployments, allowing you to run ASP.NET Core applications in a serverless environment.

Google Cloud Functions excels in integration with Google Cloud services like Cloud SQL, Firestore, and Cloud Storage. The platform's global edge network ensures low latency for applications deployed across multiple regions.

The pricing model is competitive, and the platform offers good performance characteristics. Google's expertise in distributed systems and infrastructure management translates into a robust serverless platform that can handle demanding applications.

Architectural Patterns and Best Practices

API Gateway Pattern

The API Gateway pattern is fundamental to serverless architectures. It provides a single entry point for all client requests and routes them to appropriate backend services. In the context of ASP.NET Core and serverless, the API Gateway serves as the front door to your distributed functions.

This pattern offers several advantages. It centralizes cross-cutting concerns like authentication, rate limiting, and request/response transformation. The gateway can handle API versioning, making it easier to evolve your services over time. It also provides a unified interface for clients, hiding the complexity of your backend architecture.

When implementing this pattern with ASP.NET Core, you can use services like AWS API Gateway, Azure API Management, or Google Cloud Endpoints. These services integrate seamlessly with their respective serverless platforms, providing a comprehensive solution for API management.

Event-Driven Architecture

Serverless architectures naturally lend themselves to event-driven patterns. In this approach, functions are triggered by events rather than direct HTTP requests. Events can come from various sources: database changes, file uploads, message queues, or scheduled tasks.

ASP.NET Core functions can easily integrate with event sources through platform-specific bindings. For example, an Azure Function can be triggered by a message in a Service Bus queue, or an AWS Lambda can respond to S3 bucket events. This loose coupling between components makes your system more scalable and resilient.

Event-driven architectures also enable better separation of concerns. Each function can focus on a specific business capability, making your codebase more maintainable and testable. The asynchronous nature of event processing also improves system responsiveness and throughput.

Microservices with Serverless

Serverless computing aligns perfectly with microservices architecture. Each function can represent a microservice, handling a specific business capability. This approach eliminates the operational overhead traditionally associated with microservices, such as container orchestration and service discovery.

When building microservices with ASP.NET Core and serverless, you can leverage the framework's built-in features like dependency injection, configuration management, and logging. Each microservice can be developed, deployed, and scaled independently, providing maximum flexibility and agility.

The key to success with this pattern is proper service boundaries. Each function should have a clear responsibility and minimal dependencies on other services. This approach ensures that your microservices remain loosely coupled and can evolve independently.

Data Management in Serverless ASP.NET Core

Database Integration

Data management in serverless environments requires careful consideration of connection handling and performance. Traditional approaches to database connectivity may not work efficiently in serverless contexts due to the ephemeral nature of functions.

Connection pooling becomes crucial in serverless environments. Since functions can scale rapidly, you need to manage database connections efficiently to avoid overwhelming your database. Most cloud providers offer connection pooling services that can help manage this challenge.

For ASP.NET Core applications, Entity Framework Core works well in serverless environments when configured properly. You should use the connection pooling features and consider using database-specific optimizations. Many developers also explore alternative data access patterns like the Repository pattern or direct ADO.NET for better performance in serverless contexts.

Here's an example of how to configure Entity Framework Core for optimal performance in a serverless environment:

public class Startup
{
    public void ConfigureServices(IServiceCollection services)
    {
        services.AddDbContext<ApplicationDbContext>(options =>
        {
            options.UseSqlServer(connectionString, sqlOptions =>
            {
                sqlOptions.EnableRetryOnFailure(
                    maxRetryCount: 3,
                    maxRetryDelay: TimeSpan.FromSeconds(5),
                    errorNumbersToAdd: null);
            });
        }, ServiceLifetime.Scoped);

        // Use connection pooling for better performance
        services.AddDbContextPool<ApplicationDbContext>(options =>
            options.UseSqlServer(connectionString), poolSize: 128);
    }
}

public class UserService
{
    private readonly ApplicationDbContext _context;

    public UserService(ApplicationDbContext context)
    {
        _context = context;
    }

    public async Task<User> GetUserAsync(int id)
    {
        return await _context.Users
            .AsNoTracking() // Disable change tracking for read-only operations
            .FirstOrDefaultAsync(u => u.Id == id);
    }

    public async Task<User> CreateUserAsync(CreateUserRequest request)
    {
        var user = new User 
        { 
            Name = request.Name, 
            Email = request.Email 
        };

        _context.Users.Add(user);
        await _context.SaveChangesAsync();
        return user;
    }
}

Caching Strategies

Caching in serverless environments requires different approaches compared to traditional applications. Since functions are stateless and ephemeral, you can't rely on in-memory caching across requests. Instead, you need to use external caching solutions.

Redis is a popular choice for serverless caching. Services like Azure Redis Cache, AWS ElastiCache, or Google Cloud Memorystore provide managed Redis instances that your functions can use for caching. This approach ensures that cached data is available across all function instances.

Another approach is to use the cloud provider's caching services. For example, AWS provides DynamoDB Accelerator (DAX) for DynamoDB caching, and Azure offers Azure Cache for Redis. These services are optimized for serverless workloads and provide excellent performance characteristics.

Data Persistence Patterns

Data persistence in serverless environments often involves NoSQL databases due to their scalability and performance characteristics. DynamoDB on AWS, Cosmos DB on Azure, and Firestore on Google Cloud are popular choices that integrate well with serverless platforms.

When using these databases with ASP.NET Core, you can leverage the respective SDKs and libraries. For example, the Azure Cosmos DB SDK provides excellent .NET support, making it easy to integrate with your ASP.NET Core functions.

Document-based storage patterns work particularly well in serverless contexts. Instead of complex relational designs, you can denormalize data and store it in document format. This approach reduces the number of database queries and improves performance in serverless environments.

Security Considerations

Authentication and Authorization

Security in serverless ASP.NET Core applications requires a different approach compared to traditional applications. The stateless nature of functions means that you can't rely on server-side sessions for authentication state management.

JSON Web Tokens (JWT) are commonly used for authentication in serverless environments. The token contains all necessary authentication information and can be validated by any function instance. ASP.NET Core provides excellent JWT support through the Microsoft.AspNetCore.Authentication.JwtBearer package.

Just like we discussed in our comprehensive guide on securing ASP.NET applications, implementing proper authentication and authorization is crucial for serverless applications. The principles remain the same, but the implementation details differ due to the stateless nature of serverless functions.

Cloud providers also offer identity services that integrate seamlessly with serverless platforms. AWS Cognito, Azure Active Directory, and Google Identity Platform provide comprehensive authentication and authorization capabilities. These services handle user management, token generation, and validation, reducing the security burden on your applications.

API Security

Securing APIs in serverless environments involves multiple layers of protection. At the gateway level, you can implement rate limiting, IP whitelisting, and API key validation. The cloud provider's API gateway services typically provide these features out of the box.

Input validation becomes even more critical in serverless environments due to the potential for rapid scaling and cost implications. Always validate and sanitize inputs to prevent injection attacks and ensure data integrity. ASP.NET Core's model validation features work well in serverless contexts and should be leveraged extensively.

HTTPS termination is typically handled by the cloud provider's infrastructure, but you should ensure that all communication between services is encrypted. Most cloud providers offer certificate management services that can automate SSL/TLS certificate provisioning and renewal.

Data Protection

Data protection in serverless environments requires careful consideration of encryption, both at rest and in transit. Most cloud providers offer encryption services that can be integrated with your serverless functions.

Key management is crucial for maintaining security. Services like AWS Key Management Service (KMS), Azure Key Vault, and Google Cloud KMS provide secure key storage and management capabilities. These services integrate well with serverless platforms and provide fine-grained access control.

Consider implementing encryption at the application level for sensitive data. ASP.NET Core provides data protection APIs that can be used to encrypt sensitive information before storing it in databases or caches. This approach provides an additional layer of security beyond what the cloud provider offers.

Performance Optimization

Cold Start Mitigation

Cold starts are one of the primary performance challenges in serverless environments. When a function hasn't been invoked for a while, the cloud provider needs to initialize a new container, which can introduce latency.

Several strategies can help mitigate cold starts in ASP.NET Core applications. Keeping functions warm through scheduled invocations is a common approach, though it may increase costs. Connection pooling and optimized startup code can also reduce cold start times.

The choice of deployment package size affects cold start performance. Smaller packages start faster, so consider using runtime-specific deployments and minimizing dependencies. ASP.NET Core's trimming and ahead-of-time compilation features can help reduce package sizes.

Memory and CPU Optimization

Function performance is directly related to memory allocation. Most serverless platforms allow you to configure memory, which also affects CPU allocation. Finding the right balance between memory allocation and performance is crucial for cost optimization.

ASP.NET Core applications can be optimized for serverless environments through various techniques. Using value types instead of reference types where appropriate, minimizing allocations, and leveraging object pooling can all improve performance.

Asynchronous programming patterns are particularly important in serverless environments. ASP.NET Core's async/await support should be used extensively to avoid blocking threads and improve concurrency. This approach allows your functions to handle more requests efficiently.

Monitoring and Observability

Effective monitoring is essential for serverless applications due to their distributed nature. Traditional monitoring approaches may not work well in serverless environments, so you need to adopt new strategies.

Application Performance Monitoring (APM) tools like Application Insights, AWS X-Ray, or Google Cloud Trace provide excellent visibility into serverless applications. These tools can track request flows across multiple functions and identify performance bottlenecks.

Structured logging becomes even more important in serverless environments. ASP.NET Core's logging framework integrates well with cloud provider logging services. Ensure that your logs include correlation IDs and sufficient context to trace requests across multiple functions.

Custom metrics and alerts are crucial for maintaining system health. Most cloud providers offer metrics and alerting services that can monitor function performance, error rates, and resource utilization. Set up proactive alerting to identify issues before they impact users.

Development and Deployment

Local Development

Developing serverless ASP.NET Core applications locally requires specialized tools and techniques. Most cloud providers offer local development environments that simulate their serverless platforms.

The Azure Functions Core Tools provide an excellent local development experience for Azure Functions. You can run and debug functions locally, test HTTP triggers, and integrate with local storage emulators. The tools integrate seamlessly with Visual Studio and VS Code.

AWS SAM (Serverless Application Model) provides similar capabilities for AWS Lambda development. The SAM CLI allows you to build, test, and deploy serverless applications locally. It includes features like local API Gateway simulation and step-through debugging.

Container-based development is another approach gaining popularity. You can use Docker to create local environments that closely match the serverless runtime. This approach provides consistency between development and production environments.

CI/CD for Serverless

Continuous integration and deployment for serverless applications require different approaches compared to traditional applications. The distributed nature of serverless applications means that your CI/CD pipeline needs to handle multiple functions and their dependencies.

Infrastructure as Code (IaC) becomes crucial for serverless deployments. Tools like AWS CloudFormation, Azure Resource Manager templates, or Terraform can help manage the infrastructure required for your serverless applications. This approach ensures consistency across environments and makes deployments repeatable.

Automated testing is particularly important for serverless applications due to their distributed nature. Unit tests, integration tests, and end-to-end tests should all be part of your CI/CD pipeline. Consider using tools like LocalStack or Azure Functions Core Tools to run tests against local serverless environments.

Blue-green deployments and canary releases are valuable techniques for serverless applications. Most cloud providers offer features that support these deployment patterns, allowing you to gradually roll out changes and minimize risk.

Real-Time Applications and Serverless

One interesting aspect of serverless architectures is how they handle real-time applications. While traditional approaches might use technologies like SignalR for real-time communication, serverless environments require different strategies.

Building real-time applications with SignalR in serverless environments presents unique challenges. The stateless nature of serverless functions means that maintaining persistent connections becomes more complex. However, cloud providers offer services like AWS API Gateway WebSocket API or Azure SignalR Service that can bridge this gap.

WebSocket connections can be managed through cloud services while your serverless functions handle the business logic. This hybrid approach allows you to leverage the benefits of serverless computing while still providing real-time capabilities to your users.

Identity and Access Management

Identity management in serverless applications builds upon the same principles we covered in our guide on ASP.NET Core Identity. However, the implementation details differ significantly due to the stateless nature of serverless functions.

In serverless environments, you typically rely on external identity providers and token-based authentication. The authentication flow might involve redirecting users to an identity provider, receiving tokens, and then validating those tokens in your serverless functions.

Here's an example of how to implement JWT authentication in a serverless ASP.NET Core function:

public class Startup
{
    public void ConfigureServices(IServiceCollection services)
    {
        services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)
            .AddJwtBearer(options =>
            {
                options.TokenValidationParameters = new TokenValidationParameters
                {
                    ValidateIssuer = true,
                    ValidateAudience = true,
                    ValidateLifetime = true,
                    ValidateIssuerSigningKey = true,
                    ValidIssuer = Configuration["Jwt:Issuer"],
                    ValidAudience = Configuration["Jwt:Audience"],
                    IssuerSigningKey = new SymmetricSecurityKey(
                        Encoding.UTF8.GetBytes(Configuration["Jwt:Key"]))
                };
            });

        services.AddAuthorization();
    }

    public void Configure(IApplicationBuilder app, IWebHostEnvironment env)
    {
        app.UseAuthentication();
        app.UseAuthorization();
        
        app.UseRouting();
        app.UseEndpoints(endpoints =>
        {
            endpoints.MapGet("/api/secure", [Authorize] () => "This is a secure endpoint");
        });
    }
}

Cost Optimization Strategies

Function Sizing and Scaling

Proper function sizing is crucial for cost optimization in serverless environments. Over-provisioning leads to unnecessary costs, while under-provisioning can result in poor performance and user experience.

Most serverless platforms charge based on execution time and memory allocation. Finding the optimal memory setting for your functions requires testing and monitoring. Start with conservative settings and gradually increase memory based on performance requirements.

Consider breaking down large functions into smaller, more focused ones. This approach can improve cost efficiency by ensuring that you only pay for the resources actually needed for each task. It also improves maintainability and testability.

Resource Management

Efficient resource management is essential for cost-effective serverless applications. This includes managing database connections, external service calls, and memory usage.

Connection pooling and reuse can significantly reduce costs by minimizing the overhead of establishing new connections. Consider using connection pooling libraries or services provided by your cloud provider.

Caching strategies can reduce the number of expensive operations like database queries or external API calls. Implement appropriate caching at multiple levels, including function-level caching and distributed caching.

Monitor your resource usage regularly and identify opportunities for optimization. Most cloud providers offer detailed billing and usage reports that can help you understand where your costs are coming from.

Future Trends and Considerations

Edge Computing

Edge computing is becoming increasingly important in serverless architectures. Running functions closer to users can significantly improve performance and user experience. Most cloud providers are expanding their edge computing offerings.

Content Delivery Networks (CDNs) with serverless capabilities, like Cloudflare Workers or AWS Lambda@Edge, allow you to run code at edge locations. This approach can reduce latency and improve performance for globally distributed applications.

ASP.NET Core's lightweight nature makes it well-suited for edge computing scenarios. The framework's modular design allows you to include only the necessary components, reducing the footprint required for edge deployment.

WebAssembly Integration

WebAssembly (WASM) is emerging as a promising technology for serverless computing. It provides a secure, fast, and portable runtime that can run across different platforms and environments.

Several cloud providers are exploring WebAssembly support for serverless functions. This technology could provide better performance and more consistent behavior across different cloud platforms.

.NET has strong WebAssembly support through Blazor WebAssembly, and there are ongoing efforts to improve .NET's WebAssembly capabilities for server-side scenarios. This could make ASP.NET Core applications even more suitable for serverless deployment.

AI and Machine Learning Integration

The integration of AI and machine learning capabilities with serverless architectures is becoming more common. Cloud providers are offering AI services that can be easily integrated with serverless functions.

ASP.NET Core applications can leverage these AI services through REST APIs or SDKs. This approach allows you to add intelligent features to your applications without the complexity of managing machine learning infrastructure.

Consider use cases like image recognition, natural language processing, or recommendation systems that can be implemented using serverless functions and cloud AI services. These capabilities can add significant value to your applications with minimal development effort.

Conclusion

The combination of ASP.NET Core and serverless architectures represents a powerful approach to modern application development. This partnership offers developers the ability to build scalable, cost-effective applications while leveraging the robust features and excellent developer experience that ASP.NET Core provides.

Serverless computing eliminates many of the operational challenges associated with traditional application deployment. You can focus on writing business logic rather than managing infrastructure, leading to faster development cycles and improved productivity. The automatic scaling capabilities ensure that your applications can handle varying loads efficiently while minimizing costs.

The integration between ASP.NET Core and major serverless platforms like AWS Lambda, Azure Functions, and Google Cloud Functions is mature and well-supported. Microsoft's investment in serverless compatibility means that you can leverage familiar development patterns and tools in serverless environments.

While serverless architectures introduce new challenges around cold starts, data management, and monitoring, the benefits typically outweigh these concerns for many applications. The key to success lies in understanding these challenges and implementing appropriate strategies to address them.

As the serverless ecosystem continues to evolve, we can expect even better integration, improved performance, and new capabilities that will make serverless architectures even more attractive for ASP.NET Core developers. The future of web development is increasingly serverless, and ASP.NET Core is well-positioned to be a part of that future.

Whether you're building a simple API, a complex enterprise application, or anything in between, the combination of ASP.NET Core and serverless architectures provides a compelling foundation for modern application development. The time to explore and embrace this powerful combination is now.

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