Crafting High-Performance Web APIs in C#: Essential Strategies

In today's world of demanding applications and seamless user experiences, constructing high-performance web APIs is crucial. C# and the ASP.NET Core framework provide a powerful set of tools to build APIs that excel in both speed and scalability. In this blog post, we'll explore key techniques to ensure your C# web APIs deliver optimal performance.

Key Pillars of High-Performance APIs

1. Asynchronous Programming: Embrace the power of the async and await keywords. Asynchronous operations ensure that threads are not blocked while awaiting tasks like database queries or external service calls, keeping your API responsive even under heavy loads.
2. Efficient Data Handling: Prioritize data handling efficiency by selecting a high-performance serializer like JSON.NET or exploring even faster options such as System.Text.Json. Implement content compression algorithms (like GZIP or Brotli) to reduce payload sizes and accelerate network transfer speeds. Additionally, provide server-side filtering and pagination to prevent the transfer of excessive data, enhancing client-side performance.
3. Database Optimization: Analyze slow database queries using execution plans and strategically leverage indexes for faster data retrieval. Employ Object-Relational Mappers (ORMs) like Entity Framework Core for easier database interactions, but be aware of their potential overhead and opt for raw SQL queries when fine-grained control is essential.
4. Caching: Implement caching at strategic levels. Use in-memory caching tools like IMemoryCache to store frequently used data for quick access. For larger, cluster-wide scenarios, consider distributed caching solutions like Redis. Additionally, leverage HTTP caching with browser caching and server-side caching directives (Cache-Control headers) to reduce unnecessary data transfers.
5. Profiling and Monitoring: Utilize profiling tools to pinpoint performance bottlenecks within your API code. Establish a robust monitoring system with metrics such as request latency, throughput, and error rates for proactive detection of performance issues.

Real example

Let's illustrate the concepts of asynchronous programming and in-memory caching

using Microsoft.Extensions.Caching.Memory;

public class ProductsController : ControllerBase
{
    private readonly IProductService _productService;
    private readonly IMemoryCache _cache;

    public ProductsController(IProductService productService, IMemoryCache cache)
    {
        _productService = productService;
        _cache = cache;
    }

    [HttpGet("{id}")]
    public async Task<IActionResult> GetProductById(int id)
    {
        if (_cache.TryGetValue(id, out Product product))
        {
            return Ok(product);
        }

        product = await _productService.GetProductByIdAsync(id);
        if (product == null)
        {
            return NotFound();
        }

        _cache.Set(id, product, TimeSpan.FromMinutes(1)); // Cache for 1 minute
        return Ok(product);
    }
}