Performance Optimization Techniques for .NET APIs

A comprehensive guide for optimizing .NET API performance, emphasizing the importance of using the latest .NET version, asynchronous programming, caching, pagination, minimizing exceptions, and utilizing a Content Delivery Network (CDN).

3 months ago   •   9 min read

By Stefan Đokić
Table of contents

Agenda:

  • Introduction
  • Before Optimization
  • 1) Use the Latest .NET Version
  • 2) Use async to avoid blocking calls
  • 3) Implement caching
  • 4) Use pagination
  • 5) Minimize Exceptions
  • 6) Use CDN
  • Conclusion

Introduction

In the constantly evolving realm of software development, ensuring top-tier performance, especially for .NET APIs, is not just beneficial but essential. Whether you're navigating the intricacies of the .NET Core framework or focusing on the responsiveness of your ASP.NET Core Web API, it's paramount to be equipped with effective strategies for optimization. 

As C# developers, we understand the thirst for knowledge in this domain. Thus, this article serves as a comprehensive guide, amalgamating insights from various performance enhancement methodologies, to supercharge your .NET API's speed, efficiency, and overall user experience. We'll delve deep into various techniques, from memory management to database optimizations, ensuring your applications remain a cut above the rest. 

Dive in as we unravel the secrets to maximizing the prowess of your .NET applications!

Before Optimization

Embarking on the journey of optimization without a roadmap can lead to wasted efforts, misallocated resources, and even unintended complications. Just as a doctor wouldn't prescribe medication without a proper diagnosis, developers shouldn't jump into optimization without a clear understanding of where the issues lie. 

Here's a step-by-step guide to ensuring you're well-prepared before diving into the optimization process for your .NET API. I’m using these steps.

1. Establish a Baseline:

The first and foremost step is to know your starting point. What is the current performance of your API? Having a baseline allows you to measure improvements or regressions and gives you a clear point of reference.

2. Identify Performance Bottlenecks:

Performance bottlenecks are specific areas or portions of your code that significantly degrade the overall performance. Pinpointing these areas ensures you target your optimization efforts where they can have the most impact.

3. Choose the Right Tools:

Leveraging the right diagnostic tools can make a world of difference in your optimization journey. Here are some powerful tools that I use and can help you:

  • Visual Studio Diagnostic Tools: This built-in suite in Visual Studio provides in-depth insights into various performance metrics like CPU usage and memory consumption. It's an invaluable resource to get a holistic view of your application's performance. Learn here: https://learn.microsoft.com/en-us/aspnet/core/performance/diagnostic-tools?view=aspnetcore-7.0 
  • BenchmarkDotNet: A performance-centric library, BenchmarkDotNet aids developers in crafting and executing benchmarks. This allows you to assess the efficiency of your code under different conditions, providing a granular view of where improvements can be made. Check it here: https://github.com/dotnet/BenchmarkDotNet 
  • Treblle: It helps you measure your APIs across 3 vital categories on every single request and give you a detailed report on what’s good and where you can improve.

4. Prioritize Fixes:

Not all bottlenecks are created equal. Some might be causing minor delays, while others could be responsible for significant slowdowns. Once you've identified these bottlenecks, prioritize them based on their impact on the overall user experience. This ensures that you address the most critical issues first, yielding the most significant benefits in the shortest amount of time.

Well, let me show you my optimization steps.

1) Use the Latest .NET Version

Utilizing the most recent .NET version is pivotal for optimal application performance. Here's why I think why:

Performance Boost: Newer versions come with refined and optimized runtime and libraries, leading to quicker code execution and better resource management.

Security: The latest versions encompass the most up-to-date security patches, minimizing vulnerabilities.

Bug Resolutions: Alongside security updates, newer versions rectify known issues, enhancing application stability.

Compatibility: Staying updated ensures your application is compatible with modern tools, libraries, and platforms.

Ensuring You Have the Latest Version:

  • For Visual Studio: Check for updates in the “Tools” menu under “Get Tools and Features”.
Update Visual Studio
  • .NET CLI: Run dotnet --version to see your current version and refer to the official .NET website to compare.

Check the last stable version here: https://dotnet.microsoft.com/en-us/download/dotnet/7.0 

2) Use async to avoid blocking calls

Harnessing asynchronous programming, particularly async/await in .NET, is a game-changer for developing responsive and scalable applications.

Here's a comprehensive look, complete with a practical example.

Why I think async is so important:

Responsiveness: In UI applications, async keeps the user interface snappy, irrespective of lengthy operations.

Scalability: For services like web APIs, async operations allow the handling of more simultaneous requests by not waiting on tasks, such as database queries.I will show you an example below.

Resource Efficiency: Instead of tying up threads, asynchronous operations use resources more judiciously, freeing up threads for other tasks.

Let me show you an example: Imagine you have a web service that fetches user data from a database.

If you do not use async/await:

public User FetchUserData(int userId)
{
    return Database.GetUser(userId); // This is a blocking call
}

Why this can be a problem? If Database.GetUser takes a long time, the entire method will block, holding up resources.

The solution is to introduce async/await. Let me show you how to do that:

public async Task<User> FetchUserDataAsync(int userId)
{
    return await Database.GetUserAsync(userId); // Non-blocking
}

Here, the await keyword allows the system to offload the task, freeing it to handle other operations, and making the application more responsive and scalable. 

My extra advice:

Avoid Deadlocks: Be cautious not to blend synchronous and asynchronous code without due diligence. Avoid using .Result or .Wait() on tasks.

3) Implement caching

Caching has been one of my secret weapons in the realm of application performance, especially in scenarios that involve frequent data retrieval. Let me share a personal experience.

While building an e-commerce platform, I noticed that the site began to lag as the user base grew, especially on product pages. Whenever someone accessed a product, my system would dutifully fetch the details from the database. This repeated fetching started bogging down performance, elongating page load times, and leaving users visibly frustrated.

Upon analyzing, I observed a pattern: the exact product details were fetched multiple times for various users throughout the day. 

A lightbulb moment occurred: 

"What if I could temporarily store these details after the first retrieval, so the subsequent requests wouldn’t need to hammer the database?"

So, I created a caching strategy:

With caching, instead of always querying the database, the system first checks temporary storage (or cache) for product details. If the details are found in the cache, they're returned, bypassing the database entirely. If they aren't cached, they're retrieved from the database, presented to the user, and simultaneously stored in the cache for upcoming requests.

What I used and what can you use? I utilized .NET Core's built-in caching mechanism.

Implementation:

  • Firstly, I added a caching service to the Program.cs:
builder.Services.AddMemoryCache();
  • I set up caching for the product details as follows:
public class ProductService
{
    private readonly IMemoryCache _cache;

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

    public Product GetProductDetails(int productId)
    {
        return _cache.GetOrCreate(productId, entry =>
        {
            entry.SlidingExpiration = TimeSpan.FromMinutes(10); // Cache for 10 minutes
            return FetchProductFromDatabase(productId); // My previous database fetch
        });
    }
}

The Outcome:

Noticeably Faster: My e-commerce site's response time improved drastically.

Reduced Database Stress: The reduced database hits ensured a longer, more efficient life for my database and its infrastructure.

Happy Users: The user experience was substantially smoother, leading to positive feedback.

4) Use pagination

In the digital world, data can be vast and endless. Presenting or processing all of it at once can be both overwhelming for users and taxing on system resources. 

Pagination, the technique of dividing content into separate pages, is an essential solution for this challenge. My encounter with the necessity of pagination is an illustrative tale of how a simple design decision can profoundly impact user experience and system efficiency.

My Brush with Overflowing Data:

In one of the applications I was building, there was a feature to display a list of all users. As the user base grew exponentially, this list became extensive. Every time someone tried to view the list, the system would fetch every single user from the database, causing considerable lag. Not only was the server strained, but the user interface also became cluttered and difficult to navigate.

The Power of Pagination:

Recognizing the issue, I decided to implement pagination. Here's how I approached it:

  • Limiting Records:

Instead of fetching all records, I modified the database query to retrieve a specific number of users at a time, say 20 or 50, based on the desired page size.

  • User Interface Adaptation:

The front end was adapted to display this limited set of records and provide navigation controls (like "Next", "Previous", "First", and "Last") to cycle through pages.

  • Backend Adjustments:

The API was adjusted to accept parameters for the current page and the number of records per page, allowing dynamic retrieval based on user interaction.

Let’s bring the code:

public List<User> GetPaginatedUsers(int pageNumber, int pageSize)
{
    return dbContext.Users
        .Skip((pageNumber - 1) * pageSize)
        .Take(pageSize)
        .ToList();
}

So, what have I got here?

  • Enhanced User Experience:

With fewer records displayed at once, users could navigate and find the information they needed more comfortably.

  • Reduced Server Load:

Fetching limited records reduced the strain on the server and the database, ensuring faster response times.

  • Optimized Network Traffic:

Transferring fewer records meant reduced data transfer over the network, resulting in quicker load times and less bandwidth consumption.

5) Minimize Exceptions

The Hidden Overhead of Exceptions:

During the development of an application, I implemented rigorous error handling. To ensure no critical issue went unnoticed, I liberally sprinkled exception handling across various layers of the application. The application ran smoothly, but as the load increased, I noticed a slight degradation in performance.

Diagnostics revealed a substantial number of exceptions were being thrown and caught, many of which were non-critical, like trying to find an item in a collection and throwing an exception if it wasn't present. While this approach made the application robust against unforeseen issues, it inadvertently added overhead.

What did I find as a solution?

The Elegance of Result Object:

A Result object encapsulates the outcome of an operation in a clean and expressive manner. It's designed to convey the result explicitly, without relying on exceptions. The beauty lies in its simplicity:

public class Result<T>
{
    public bool IsSuccess { get; }
    public T Value { get; }
    public string Error { get; }

    protected Result(T value, bool isSuccess, string error)
    {
        IsSuccess = isSuccess;
        Value = value;
        Error = error;
    }

    public static Result<T> Success(T value) => new Result<T>(value, true, null);
    public static Result<T> Failure(string error) => new Result<T>(default(T), false, error);
}

Okay, so what can you do with this? If we take some real-world examples. Let me show you. 

Traditional approach with exceptions:

public User GetUser(int userId)
{
    if(!database.Contains(userId))
    {
        throw new UserNotFoundException();
    }
    return database.GetUser(userId);
}

With the Result paradigm:

public Result<User> GetUser(int userId)
{
    if(!database.Contains(userId))
    {
        return Result<User>.Failure("User not found.");
    }
    return Result<User>.Success(database.GetUser(userId));
}

So why use the Result object?

  • Expressiveness: By just looking at the function signature, one can deduce the possible outcomes, making the code self-documenting.
  • Performance: This paradigm avoids the overhead associated with throwing and catching exceptions, especially in expected error scenarios.
  • Unified Error Handling: Errors are now values that can be passed around, manipulated, or logged, making error handling more uniform and predictable.
  • Extensibility: It's easy to extend the Result class to carry additional metadata, validation errors, or other contextual information.

6) Use CDN

What is a CDN?

A Content Delivery Network (CDN) is a collection of servers distributed across various global locations. These servers store cached versions of your static and sometimes dynamic content. When a user makes a request, instead of accessing your primary server, they are routed to the nearest CDN server, resulting in significantly faster response times.

If you are using third-party libraries for CSS and JavaScript that have CDN versions available, then try using the CDN file path rather than the downloaded library file. A CDN can serve static assets like images, stylesheets, and JavaScript files from locations closer to the user, reducing the time needed for these assets to travel across the network.

Example:

<!-- Include static assets from a CDN -->
<link rel="stylesheet" href="https://cdn.example.com/styles.css">
<script src="https://cdn.example.com/script.js"></script>

Why Use a CDN for API Optimization?

  • Reduced Latency: By serving content from a location closer to the end user, CDNs drastically decrease the time taken to fetch data, ensuring swift responses.
  • Load Distribution: CDNs share the traffic load with the primary server, preventing it from becoming a bottleneck and potentially reducing downtimes during traffic surges.
  • Enhanced Reliability: If one server within the CDN faces issues, requests are automatically redirected to another available server.
  • Improved Security: CDNs often come with built-in security measures like DDoS protection, adding an extra layer of safety for your application.

How to Use a CDN?

  • Choose a Provider: There are numerous CDN providers available, like Akamai, Cloudflare, and AWS CloudFront. Select one that aligns with your needs and budget.
  • Configure Your Content: Integrate the CDN with your application, ensuring that the static (and in some cases, dynamic) content is cached appropriately on the CDN.
  • Update DNS Settings: Point your application’s domain or subdomain to the CDN provider, so requests are correctly routed through the CDN.

Conclusion

Optimizing API performance is essential in our digital world. Throughout our exploration of strategies—from the latest .NET versions to CDN integration—it's evident that an efficient API requires consistent monitoring and adaptive strategies. Tools and practices like caching, database optimization, and asynchronous programming showcase the evolution and depth of performance enhancement techniques.

However, the key takeaway is the continuous nature of this journey. Performance isn't a one-time achievement but an ongoing commitment. Regular updates, vigilant monitoring, and in-depth analysis are crucial. As user expectations grow and the tech landscape shifts, staying proactive and user-centric will ensure that APIs consistently deliver top-notch performance.

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