ASP.NET Core Performance Best Practices

Introduction

Achieving high performance in ASP.NET Core applications is crucial for delivering a responsive and scalable user experience. This document outlines key strategies and best practices to optimize your .NET Core web applications.

Key Optimization Strategies

Caching

Caching is one of the most effective ways to improve performance by reducing redundant computations and data retrieval. ASP.NET Core offers built-in support for various caching mechanisms.

• In-Memory Caching: Ideal for frequently accessed, small amounts of data. Use IMemoryCache.
• Distributed Caching: For scenarios where cache needs to be shared across multiple application instances (e.g., using Redis or SQL Server). Use IDistributedCache.
• Response Caching: Cache entire HTTP responses to avoid reprocessing requests.

Example using IMemoryCache:

using Microsoft.Extensions.Caching.Memory;

public class MyService
{
    private readonly IMemoryCache _cache;

    public MyService(IMemoryCache cache)
    {
        _cache = cache;
    }

    public string GetData(int id)
    {
        string cacheKey = $"data_{id}";
        if (_cache.TryGetValue(cacheKey, out string cachedData))
        {
            return cachedData;
        }

        // Simulate data retrieval
        var data = $"Data for {id}"; 

        var cacheEntryOptions = new MemoryCacheEntryOptions()
            .SetSlidingExpiration(TimeSpan.FromMinutes(5)); // Cache for 5 minutes

        _cache.Set(cacheKey, data, cacheEntryOptions);
        return data;
    }
}
        

Data Access Optimization

Inefficient data access can be a major bottleneck. Consider the following:

• Efficient Queries: Only retrieve the data you need. Use LINQ projection and avoid N+1 query problems.
• Asynchronous Operations: Use asynchronous methods (e.g., ToListAsync(), FirstOrDefaultAsync()) for I/O-bound operations to free up threads.
• Connection Pooling: Ensure your database provider is configured for efficient connection pooling.
• Batching: For large numbers of inserts or updates, consider batching operations.

Code Efficiency

• Minimize Allocations: Avoid unnecessary object allocations, especially in performance-critical loops. Use structs where appropriate and consider Span<T> and Memory<T> for low-allocation string manipulation.
• Efficient Algorithms: Choose algorithms with better time complexity.
• Avoid Synchronous I/O: Never block on asynchronous operations using .Result or .Wait() in ASP.NET Core request processing pipelines, as this can lead to thread pool starvation and deadlocks.
• Optimized Serialization: Consider using faster JSON serializers like System.Text.Json (built-in) or Utf8Json over older ones like Newtonsoft.Json for high-throughput scenarios.

// Example of efficient string concatenation
// Instead of: string result = item1 + item2 + item3;
// Use:
var builder = new System.Text.StringBuilder();
builder.Append(item1);
builder.Append(item2);
builder.Append(item3);
string result = builder.ToString();
        

HTTP Protocol Optimizations

• HTTP/2 and HTTP/3: Enable these protocols for multiplexing, header compression, and reduced latency.
• Gzip Compression: Configure your server to use Gzip compression for responses to reduce bandwidth. ASP.NET Core has built-in middleware for this.
• Minimize Round Trips: Bundle CSS and JavaScript files.

Dependency Injection

While DI is a core feature, be mindful of the lifetime of your services:

• Scoped and Singleton: Prefer Scoped or Singleton lifetimes for services that don't hold per-request state. Avoid Transient for services that are frequently resolved, as it leads to more overhead.
• Lazy Initialization: For expensive-to-create singletons, consider lazy initialization.

Monitoring and Profiling

You can't optimize what you don't measure. Use these tools:

• Application Insights: For real-time monitoring of performance, exceptions, and dependencies in production.
• Kudu/App Service Editor: For inspecting file system, logs, and basic diagnostics on Azure.
• Visual Studio Profiler: For detailed CPU, memory, and I/O profiling during development.
• BenchmarkDotNet: For micro-benchmarking specific code segments.
• ILogger: Implement structured logging to track performance metrics and identify slow operations.

Advanced Techniques

• Background Tasks: Offload long-running or CPU-intensive tasks to background services or queues (e.g., Hangfire, Azure Functions, Azure Service Bus).
• Compiled Expressions: For highly repetitive LINQ queries, consider compiling them to improve performance.
• Native AOT: For specific deployment scenarios, consider Native AOT compilation for faster startup times and reduced memory footprint.
• Optimizing Middleware Pipeline: Ensure your middleware pipeline is lean and efficient, removing any unnecessary components.

By implementing these strategies, you can significantly enhance the performance and scalability of your ASP.NET Core applications.