Rate Limiting

Core Principles

• Protect backend resources from overload and abuse
• Ensure fair access across consumers — no single client starves others
• Return 429 Too Many Requests with a Retry-After header when limits are exceeded
• Apply rate limiting as middleware early in the pipeline, before expensive work
• Use the built-in System.Threading.RateLimiting and Microsoft.AspNetCore.RateLimiting packages (.NET 7+)
• Combine global and per-endpoint policies for layered protection

When to Use

• Public-facing APIs exposed to untrusted or semi-trusted clients
• Endpoints with expensive downstream operations (database writes, external API calls)
• Multi-tenant systems where one tenant's traffic must not degrade others
• Authentication endpoints to prevent brute-force attacks
• Any API that needs to enforce usage quotas or SLA tiers

When NOT to Use

• Internal service-to-service calls behind a trusted network boundary (use circuit breakers instead)
• Static file serving already handled by a CDN or reverse proxy
• When an upstream API gateway (e.g., Azure API Management, Kong) already enforces limits
• Low-traffic admin endpoints where throttling adds complexity without benefit

Patterns

Setup

// Program.cs
using System.Threading.RateLimiting;
using Microsoft.AspNetCore.RateLimiting;

builder.Services.AddRateLimiter(options =>
{
    options.RejectionStatusCode = StatusCodes.Status429TooManyRequests;

    // Global limiter applied to all endpoints
    options.GlobalLimiter = PartitionedRateLimiter.Create<HttpContext, string>(
        context => RateLimitPartition.GetFixedWindowLimiter(
            partitionKey: "global",
            factory: _ => new FixedWindowRateLimiterOptions
            {
                PermitLimit = 1000,
                Window = TimeSpan.FromMinutes(1)
            }));
});

// Add middleware — place after authentication but before endpoint routing
app.UseRateLimiter();

Fixed Window

Allows a fixed number of requests within a non-overlapping time window. Simplest algorithm but can cause burst traffic at window boundaries.

builder.Services.AddRateLimiter(options =>
{
    options.AddFixedWindowLimiter("fixed", limiterOptions =>
    {
        limiterOptions.PermitLimit = 100;
        limiterOptions.Window = TimeSpan.FromMinutes(1);
        limiterOptions.QueueProcessingOrder = QueueProcessingOrder.OldestFirst;
        limiterOptions.QueueLimit = 10;
    });
});

Sliding Window

Divides the window into segments for smoother traffic distribution. Avoids the boundary-burst problem of fixed windows.

builder.Services.AddRateLimiter(options =>
{
    options.AddSlidingWindowLimiter("sliding", limiterOptions =>
    {
        limiterOptions.PermitLimit = 100;
        limiterOptions.Window = TimeSpan.FromMinutes(1);
        limiterOptions.SegmentsPerWindow = 6; // 10-second segments
        limiterOptions.QueueProcessingOrder = QueueProcessingOrder.OldestFirst;
        limiterOptions.QueueLimit = 5;
    });
});

Token Bucket

Tokens replenish at a steady rate, allowing short bursts up to the bucket capacity while enforcing a long-term average rate.

builder.Services.AddRateLimiter(options =>
{
    options.AddTokenBucketLimiter("token", limiterOptions =>
    {
        limiterOptions.TokenLimit = 100;
        limiterOptions.ReplenishmentPeriod = TimeSpan.FromSeconds(10);
        limiterOptions.TokensPerPeriod = 20;
        limiterOptions.QueueProcessingOrder = QueueProcessingOrder.OldestFirst;
        limiterOptions.QueueLimit = 10;
        limiterOptions.AutoReplenishment = true;
    });
});

Concurrency Limiter

Limits the number of concurrent requests rather than requests per time window. Useful for protecting resources with limited parallelism.

builder.Services.AddRateLimiter(options =>
{
    options.AddConcurrencyLimiter("concurrency", limiterOptions =>
    {
        limiterOptions.PermitLimit = 50;
        limiterOptions.QueueProcessingOrder = QueueProcessingOrder.OldestFirst;
        limiterOptions.QueueLimit = 25;
    });
});

Per-Endpoint Policies

Apply named policies to specific endpoints or route groups.

// Minimal API
app.MapGet("/api/orders", GetOrders)
    .RequireRateLimiting("sliding");

app.MapPost("/api/orders", CreateOrder)
    .RequireRateLimiting("token");

// Route group
var api = app.MapGroup("/api/reports")
    .RequireRateLimiting("fixed");

api.MapGet("/daily", GetDailyReport);
api.MapGet("/monthly", GetMonthlyReport);

// Disable rate limiting on a specific endpoint
app.MapGet("/api/health", GetHealth)
    .DisableRateLimiting();

// Controller attribute
[EnableRateLimiting("sliding")]
[ApiController]
[Route("api/[controller]")]
public sealed class OrdersController : ControllerBase
{
    [HttpGet]
    public async Task<IActionResult> GetOrders() { /* ... */ }

    [DisableRateLimiting]
    [HttpGet("count")]
    public async Task<IActionResult> GetOrderCount() { /* ... */ }
}

Custom Partitioners

Partition rate limits by user identity, IP address, or API key so each consumer gets an independent quota.

builder.Services.AddRateLimiter(options =>
{
    // Per authenticated user
    options.AddPolicy("per-user", context =>
        RateLimitPartition.GetFixedWindowLimiter(
            partitionKey: context.User?.Identity?.Name ?? "anonymous",
            factory: _ => new FixedWindowRateLimiterOptions
            {
                PermitLimit = 60,
                Window = TimeSpan.FromMinutes(1)
            }));

    // Per IP address
    options.AddPolicy("per-ip", context =>
        RateLimitPartition.GetSlidingWindowLimiter(
            partitionKey: context.Connection.RemoteIpAddress?.ToString() ?? "unknown",
            factory: _ => new SlidingWindowRateLimiterOptions
            {
                PermitLimit = 200,
                Window = TimeSpan.FromMinutes(1),
                SegmentsPerWindow = 4
            }));

    // Per API key with tiered limits
    options.AddPolicy("per-api-key", context =>
    {
        var apiKey = context.Request.Headers["X-Api-Key"].ToString();
        var tier = GetTierForApiKey(apiKey); // Your lookup logic

        return tier switch
        {
            "premium" => RateLimitPartition.GetTokenBucketLimiter(apiKey,
                _ => new TokenBucketRateLimiterOptions
                {
                    TokenLimit = 500,
                    ReplenishmentPeriod = TimeSpan.FromSeconds(10),
                    TokensPerPeriod = 100,
                    AutoReplenishment = true
                }),
            _ => RateLimitPartition.GetTokenBucketLimiter(apiKey,
                _ => new TokenBucketRateLimiterOptions
                {
                    TokenLimit = 50,
                    ReplenishmentPeriod = TimeSpan.FromSeconds(10),
                    TokensPerPeriod = 10,
                    AutoReplenishment = true
                })
        };
    });
});

429 Response

Customize the rejection response to include a Retry-After header and a structured error body.

builder.Services.AddRateLimiter(options =>
{
    options.RejectionStatusCode = StatusCodes.Status429TooManyRequests;

    options.OnRejected = async (context, cancellationToken) =>
    {
        context.HttpContext.Response.StatusCode = StatusCodes.Status429TooManyRequests;

        if (context.Lease.TryGetMetadata(MetadataName.RetryAfter, out var retryAfter))
        {
            context.HttpContext.Response.Headers.RetryAfter =
                ((int)retryAfter.TotalSeconds).ToString();
        }

        context.HttpContext.Response.ContentType = "application/problem+json";
        await context.HttpContext.Response.WriteAsJsonAsync(new
        {
            type = "https://tools.ietf.org/html/rfc6585#section-4",
            title = "Too Many Requests",
            status = 429,
            detail = "Rate limit exceeded. Please retry after the duration indicated in the Retry-After header."
        }, cancellationToken);
    };
});

Decision Guide

Scenario	Algorithm	Why
Simple request cap per minute	Fixed Window	Easy to understand and configure
Smooth traffic with no boundary spikes	Sliding Window	Distributes permits across segments
Allow short bursts with steady average	Token Bucket	Permits accumulate during quiet periods
Protect CPU/memory-bound operations	Concurrency Limiter	Caps parallel execution, not rate
Multi-tenant with per-user fairness	Custom Partitioner + any algorithm	Each partition tracks independently
Login / auth endpoints (brute force)	Fixed Window, low limit	Simple hard cap per IP
File upload endpoints	Concurrency Limiter	Prevent memory exhaustion from parallel uploads
Public search API	Sliding Window	Smooth throttling for variable traffic

Anti-Patterns

Anti-Pattern	Problem	Fix
No Retry-After header on 429	Clients retry immediately, worsening load	Use OnRejected to set the header from lease metadata
Rate limiting after expensive middleware	Work is already done before rejection	Place UseRateLimiter() early in the pipeline
Same limit for all endpoints	Health checks and admin routes get throttled	Use per-endpoint policies and DisableRateLimiting()
Global-only limits, no per-client partitioning	One abusive client exhausts the quota for everyone	Use AddPolicy with a partition key (user, IP, API key)
Unlimited queue depth	Memory grows under sustained overload	Set QueueLimit to a reasonable bound
Hardcoded limits with no configuration	Cannot adjust without redeployment	Bind limits from IConfiguration / appsettings.json
Rate limiting in every microservice independently	Inconsistent limits, hard to reason about	Centralize at the API gateway when possible

Detect Existing Patterns

1. Search for Microsoft.AspNetCore.RateLimiting package in .csproj files
2. Look for AddRateLimiter in Program.cs or startup configuration
3. Check for UseRateLimiter() in the middleware pipeline
4. Search for RequireRateLimiting or EnableRateLimiting on endpoints
5. Look for third-party packages like AspNetCoreRateLimit (migration candidate)

Adding to Existing Project

1. Verify .NET 7 or later — rate limiting middleware is not available in earlier versions
2. Install Microsoft.AspNetCore.RateLimiting (included in the framework shared package)
3. Register AddRateLimiter() with at least one named policy
4. Add middleware app.UseRateLimiter() after authentication, before endpoint mapping
5. Apply policies to endpoints with RequireRateLimiting("policy-name")
6. Configure OnRejected to return Retry-After and a Problem Details body
7. Test with a load tool (e.g., dotnet-httpie, bombardier) to verify limits

References

• https://learn.microsoft.com/en-us/aspnet/core/performance/rate-limit
• https://devblogs.microsoft.com/dotnet/announcing-rate-limiting-for-dotnet/
• https://learn.microsoft.com/en-us/dotnet/api/system.threading.ratelimiting