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ASP.NET Core Performance Best Practices
Tips for increasing performance in ASP.NET Core apps and avoiding common performance problems.
>= aspnetcore-2.1

ASP.NET Core Performance Best Practices

By Mike Rousos

This article provides guidelines for performance best practices with ASP.NET Core.

Cache aggressively

Caching is discussed in several parts of this document. For more information, see xref:performance/caching/response.

Understand hot code paths

In this document, a hot code path is defined as a code path that is frequently called and where much of the execution time occurs. Hot code paths typically limit app scale-out and performance and are discussed in several parts of this document.

Avoid blocking calls

ASP.NET Core apps should be designed to process many requests simultaneously. Asynchronous APIs allow a small pool of threads to handle thousands of concurrent requests by not waiting on blocking calls. Rather than waiting on a long-running synchronous task to complete, the thread can work on another request.

A common performance problem in ASP.NET Core apps is blocking calls that could be asynchronous. Many synchronous blocking calls lead to Thread Pool starvation and degraded response times.

Do not:

  • Block asynchronous execution by calling Task.Wait or Task.Result.
  • Acquire locks in common code paths. ASP.NET Core apps are most performant when architected to run code in parallel.
  • Call Task.Run and immediately await it. ASP.NET Core already runs app code on normal Thread Pool threads, so calling Task.Run only results in extra unnecessary Thread Pool scheduling. Even if the scheduled code would block a thread, Task.Run does not prevent that.


  • Make hot code paths asynchronous.
  • Call data access and long-running operations APIs asynchronously if an asynchronous API is available. Once again, do not use Task.Run to make a synchronus API asynchronous.
  • Make controller/Razor Page actions asynchronous. The entire call stack is asynchronous in order to benefit from async/await patterns.

A profiler, such as PerfView, can be used to find threads frequently added to the Thread Pool. The Microsoft-Windows-DotNETRuntime/ThreadPoolWorkerThread/Start event indicates a thread added to the thread pool.

Minimize large object allocations

The .NET Core garbage collector manages allocation and release of memory automatically in ASP.NET Core apps. Automatic garbage collection generally means that developers don't need to worry about how or when memory is freed. However, cleaning up unreferenced objects takes CPU time, so developers should minimize allocating objects in hot code paths. Garbage collection is especially expensive on large objects (> 85 K bytes). Large objects are stored on the large object heap and require a full (generation 2) garbage collection to clean up. Unlike generation 0 and generation 1 collections, a generation 2 collection requires a temporary suspension of app execution. Frequent allocation and de-allocation of large objects can cause inconsistent performance.


  • Do consider caching large objects that are frequently used. Caching large objects prevents expensive allocations.
  • Do pool buffers by using an ArrayPool<T> to store large arrays.
  • Do not allocate many, short-lived large objects on hot code paths.

Memory issues, such as the preceding, can be diagnosed by reviewing garbage collection (GC) stats in PerfView and examining:

  • Garbage collection pause time.
  • What percentage of the processor time is spent in garbage collection.
  • How many garbage collections are generation 0, 1, and 2.

For more information, see Garbage Collection and Performance.

Optimize Data Access

Interactions with a data store and other remote services are often the slowest parts of an ASP.NET Core app. Reading and writing data efficiently is critical for good performance.


  • Do call all data access APIs asynchronously.
  • Do not retrieve more data than is necessary. Write queries to return just the data that's necessary for the current HTTP request.
  • Do consider caching frequently accessed data retrieved from a database or remote service if slightly out-of-date data is acceptable. Depending on the scenario, use a MemoryCache or a DistributedCache. For more information, see xref:performance/caching/response.
  • Do minimize network round trips. The goal is to retrieve the required data in a single call rather than several calls.
  • Do use no-tracking queries in Entity Framework Core when accessing data for read-only purposes. EF Core can return the results of no-tracking queries more efficiently.
  • Do filter and aggregate LINQ queries (with .Where, .Select, or .Sum statements, for example) so that the filtering is performed by the database.
  • Do consider that EF Core resolves some query operators on the client, which may lead to inefficient query execution. For more information, see Client evaluation performance issues.
  • Do not use projection queries on collections, which can result in executing "N + 1" SQL queries. For more information, see Optimization of correlated subqueries.

See EF High Performance for approaches that may improve performance in high-scale apps:

We recommend measuring the impact of the preceding high-performance approaches before committing the code base. The additional complexity of compiled queries may not justify the performance improvement.

Query issues can be detected by reviewing the time spent accessing data with Application Insights or with profiling tools. Most databases also make statistics available concerning frequently executed queries.

Pool HTTP connections with HttpClientFactory

Although HttpClient implements the IDisposable interface, it's designed for reuse. Closed HttpClient instances leave sockets open in the TIME_WAIT state for a short period of time. If a code path that creates and disposes of HttpClient objects is frequently used, the app may exhaust available sockets. HttpClientFactory was introduced in ASP.NET Core 2.1 as a solution to this problem. It handles pooling HTTP connections to optimize performance and reliability.


Keep common code paths fast

You want all of your code to be fast, frequently called code paths are the most critical to optimize:

  • Middleware components in the app's request processing pipeline, especially middleware run early in the pipeline. These components have a large impact on performance.
  • Code that's executed for every request or multiple times per request. For example, custom logging, authorization handlers, or initialization of transient services.


Complete long-running Tasks outside of HTTP requests

Most requests to an ASP.NET Core app can be handled by a controller or page model calling necessary services and returning an HTTP response. For some requests that involve long-running tasks, it's better to make the entire request-response process asynchronous.


  • Do not wait for long-running tasks to complete as part of ordinary HTTP request processing.
  • Do consider handling long-running requests with background services or out of process with an Azure Function. Completing work out-of-process is especially beneficial for CPU-intensive tasks.
  • Do use real-time communication options, such as SignalR, to communicate with clients asynchronously.

Minify client assets

ASP.NET Core apps with complex front-ends frequently serve many JavaScript, CSS, or image files. Performance of initial load requests can be improved by:

  • Bundling, which combines multiple files into one.
  • Minifying, which reduces the size of files by removing whitespace and comments.


  • Do use ASP.NET Core's built-in support for bundling and minifying client assets.
  • Do consider other third-party tools, such as Webpack, for complex client asset management.

Compress responses

Reducing the size of the response usually increases the responsiveness of an app, often dramatically. One way to reduce payload sizes is to compress an app's responses. For more information, see Response compression.

Use the latest ASP.NET Core release

Each new release of ASP.NET Core includes performance improvements. Optimizations in .NET Core and ASP.NET Core mean that newer versions generally outperform older versions. For example, .NET Core 2.1 added support for compiled regular expressions and benefitted from Span<T>. ASP.NET Core 2.2 added support for HTTP/2. ASP.NET Core 3.0 adds many improvements that reduce memory usage and improve throughput. If performance is a priority, consider upgrading to the current version of ASP.NET Core.

Minimize exceptions

Exceptions should be rare. Throwing and catching exceptions is slow relative to other code flow patterns. Because of this, exceptions shouldn't be used to control normal program flow.


  • Do not use throwing or catching exceptions as a means of normal program flow, especially in hot code paths.
  • Do include logic in the app to detect and handle conditions that would cause an exception.
  • Do throw or catch exceptions for unusual or unexpected conditions.

App diagnostic tools, such as Application Insights, can help to identify common exceptions in an app that may affect performance.

Performance and reliability

The following sections provide performance tips and known reliability problems and solutions.

Avoid synchronous read or write on HttpRequest/HttpResponse body

All IO in ASP.NET Core is asynchronous. Servers implement the Stream interface, which has both synchronous and asynchronous overloads. The asynchronous ones should be preferred to avoid blocking thread pool threads. Blocking threads can lead to thread pool starvation.

Do not do this: The following example uses the xref:System.IO.StreamReader.ReadToEnd*. It blocks the current thread to wait for the result. This is an example of sync over async.


In the preceding code, Get synchronously reads the entire HTTP request body into memory. If the client is slowly uploading, the app is doing sync over async. The app does sync over async because Kestrel does NOT support synchronous reads.

Do this: The following example uses xref:System.IO.StreamReader.ReadToEndAsync* and does not block the thread while reading.


The preceding code asynchronously reads the entire HTTP request body into memory.

[!WARNING] If the request is large, reading the entire HTTP request body into memory could lead to an out of memory (OOM) condition. OOM can result in a Denial Of Service. For more information, see Avoid reading large request bodies or response bodies into memory in this document.

Do this: The following example is fully asynchronous using a non buffered request body:


The preceding code asynchronously de-serializes the request body into a C# object.

Prefer ReadFormAsync over Request.Form

Use HttpContext.Request.ReadFormAsync instead of HttpContext.Request.Form. HttpContext.Request.Form can be safely read only with the following conditions:

  • The form has been read by a call to ReadFormAsync, and
  • The cached form value is being read using HttpContext.Request.Form

Do not do this: The following example uses HttpContext.Request.Form. HttpContext.Request.Form uses sync over async and can lead to thread pool starvation.


Do this: The following example uses HttpContext.Request.ReadFormAsync to read the form body asynchronously.


Avoid reading large request bodies or response bodies into memory

In .NET, every object allocation greater than 85 KB ends up in the large object heap (LOH). Large objects are expensive in two ways:

  • The allocation cost is high because the memory for a newly allocated large object has to be cleared. The CLR guarantees that memory for all newly allocated objects is cleared.
  • LOH is collected with the rest of the heap. LOH requires a full garbage collection or Gen2 collection.

This blog post describes the problem succinctly:

When a large object is allocated, it’s marked as Gen 2 object. Not Gen 0 as for small objects. The consequences are that if you run out of memory in LOH, GC cleans up the whole managed heap, not only LOH. So it cleans up Gen 0, Gen 1 and Gen 2 including LOH. This is called full garbage collection and is the most time-consuming garbage collection. For many applications, it can be acceptable. But definitely not for high-performance web servers, where few big memory buffers are needed to handle an average web request (read from a socket, decompress, decode JSON & more).

Naively storing a large request or response body into a single byte[] or string:

  • May result in quickly running out of space in the LOH.
  • May cause performance issues for the app because of full GCs running.

Working with a synchronous data processing API

When using a serializer/de-serializer that only supports synchronous reads and writes (for example, JSON.NET):

  • Buffer the data into memory asynchronously before passing it into the serializer/de-serializer.

[!WARNING] If the request is large, it could lead to an out of memory (OOM) condition. OOM can result in a Denial Of Service. For more information, see Avoid reading large request bodies or response bodies into memory in this document.

ASP.NET Core 3.0 uses xref:System.Text.Json by default for JSON serialization. xref:System.Text.Json:

  • Reads and writes JSON asynchronously.
  • Is optimized for UTF-8 text.
  • Typically higher performance than Newtonsoft.Json.

Do not store IHttpContextAccessor.HttpContext in a field

The IHttpContextAccessor.HttpContext returns the HttpContext of the active request when accessed from the request thread. The IHttpContextAccessor.HttpContext should not be stored in a field or variable.

Do not do this: The following example stores the HttpContext in a field, and then attempts to use it later.


The preceding code frequently captures a null or incorrect HttpContext in the constructor.

Do this: The following example:

  • Stores the xref:Microsoft.AspNetCore.Http.IHttpContextAccessor in a field.
  • Uses the HttpContext field at the correct time and checks for null.


Do not access HttpContext from multiple threads

HttpContext is NOT thread-safe. Accessing HttpContext from multiple threads in parallel can result in undefined behavior such as hangs, crashes, and data corruption.

Do not do this: The following example makes three parallel requests and logs the incoming request path before and after the outgoing HTTP request. The request path is accessed from multiple threads, potentially in parallel.


Do this: The following example copies all data from the incoming request before making the three parallel requests.


Do not use the HttpContext after the request is complete

HttpContext is only valid as long as there is an active HTTP request in the ASP.NET Core pipeline. The entire ASP.NET Core pipeline is an asynchronous chain of delegates that executes every request. When the Task returned from this chain completes, the HttpContext is recycled.

Do not do this: The following example uses async void which makes the HTTP request complete when the first await is reached:

  • Which is ALWAYS a bad practice in ASP.NET Core apps.
  • Accesses the HttpResponse after the HTTP request is complete.
  • Crashes the process.


Do this: The following example returns a Task to the framework so the HTTP request doesn't complete until the action completes.


Do not capture the HttpContext in background threads

Do not do this: The following example shows a closure is capturing the HttpContext from the Controller property. This is a bad practice because the work item could:

  • Run outside of the request scope.
  • Attempt to read the wrong HttpContext.


Do this: The following example:

  • Copies the data required in the background task during the request.
  • Doesn't reference anything from the controller.


Background tasks should be implemented as hosted services. For more information, see Background tasks with hosted services.

Do not capture services injected into the controllers on background threads

Do not do this: The following example shows a closure is capturing the DbContext from the Controller action parameter. This is a bad practice. The work item could run outside of the request scope. The ContosoDbContext is scoped to the request, resulting in an ObjectDisposedException.


Do this: The following example:

  • Injects an xref:Microsoft.Extensions.DependencyInjection.IServiceScopeFactory in order to create a scope in the background work item. IServiceScopeFactory is a singleton.
  • Creates a new dependency injection scope in the background thread.
  • Doesn't reference anything from the controller.
  • Doesn't capture the ContosoDbContext from the incoming request.


The following highlighted code:

  • Creates a scope for the lifetime of the background operation and resolves services from it.
  • Uses ContosoDbContext from the correct scope.


Do not modify the status code or headers after the response body has started

ASP.NET Core does not buffer the HTTP response body. The first time the response is written:

  • The headers are sent along with that chunk of the body to the client.
  • It's no longer possible to change response headers.

Do not do this: The following code tries to add response headers after the response has already started:


In the preceding code, context.Response.Headers["test"] = "test value"; will throw an exception if next() has written to the response.

Do this: The following example checks if the HTTP response has started before modifying the headers.


Do this: The following example uses HttpResponse.OnStarting to set the headers before the response headers are flushed to the client.

Checking if the response has not started allows registering a callback that will be invoked just before response headers are written. Checking if the response has not started:

  • Provides the ability to append or override headers just in time.
  • Doesn't require knowledge of the next middleware in the pipeline.


Do not call next() if you have already started writing to the response body

Components only expect to be called if it's possible for them to handle and manipulate the response.

You can’t perform that action at this time.