HTTP/3 Support

.NET 8 integrates native support for HTTP/3, the newest version of the HTTP protocol, which offers benefits such as:

• Enhanced Reliability: The QUIC protocol provides built-in error correction, improving reliability on unstable networks.

Performance Improvements in the Core Framework

.NET 8 introduces several significant enhancements, including:

• Faster JSON Serialization/Deserialization: Improved processing speeds for JSON, a common data format in APIs.
• Optimized Memory Management: Enhanced memory usage to lower the overhead associated with API requests.

Minimal APIs Enhancements

• Efficiency: Write less code to achieve more, a significant benefit for today's developers.
• Performance: Minimal APIs are quick and well-suited for high-performance applications.
• User-Friendly: They are straightforward and easy to understand.
• Flexibility: Appropriate for various application types, from microservices to extensive systems.

We will also discuss examples of Minimal APIs in .NET 8 using OpenAPI:

To utilize OpenAPI documentation features, you need the Microsoft.AspNetCore.OpenApi package. Install it via the Package Manager Console with the following command:

This package is crucial for using the WithOpenApi extension methods featured in the examples below.

Example 1: Hello World!

This API responds with a “Hello World!” message. Your API can be accessed at http://localhost:<port>/, with the port number varying according to your configuration.

The following code illustrates this:

Before exploring the routes, let’s examine the setup. An IBookService interface and its implementation, BookService, are created to simulate a book database. This structure demonstrates the encapsulation of data access logic within a service layer, promoting separation of concerns and enhancing code maintainability.

The IBookService interface acts as our framework, detailing the functionalities required — listing all books and retrieving a specific book by its ID. BookService is the concrete implementation that describes how these functionalities work.

Within BookService, a private list _books serves as our mock database, pre-loaded with a few books for simulation, allowing us to focus on API functionality without actual database concerns.

The GetBooks method returns all books, and GetBook utilizes LINQ to find a book by its ID, providing a straightforward yet effective data management approach.

Example 2: Fetching All Books

This example demonstrates how to retrieve the entire list of books available in the library.

• Endpoint Definition: app.MapGet(“/books”, …): Establishes a GET endpoint at the URL /books.
• Dependency Injection: (IBookService bookService): Automatically injects the IBookService, allowing access to the book service.
• Service Interaction: bookService.GetBooks() calls the GetBooks method from BookService to retrieve all books.
• Response: TypedResults.Ok(…): Wraps the book list in an HTTP 200 OK response.
• You can make a GET request to https://localhost:<port>/books via Postman or a browser to receive a JSON list of all books.
• Swagger Documentation:
  1. WithName(“GetBooks”): Provides a descriptive name for the endpoint.
  2. WithOpenApi(…): Adds informative details for the Swagger UI, enhancing API documentation.

Example 3: Fetching a Book by ID

This example illustrates how to retrieve a specific book using its ID.

• Endpoint Definition: app.MapGet(“/books/{id}”, …): Sets up a GET endpoint at /books/{id}, where {id} signifies the book ID.
• Route Logic: bookService.GetBook(id): Attempts to find the book by its ID. If the book exists, the result is not null.
• Swagger Documentation: Similar to Example 2, it provides useful information for the Swagger UI.

To retrieve a book with ID 2, send a GET request to https://localhost:<port>/books/2. You will either receive the book's details in JSON format or a 404 Not Found response if the ID is invalid.

• Conditional Response:
  1. If found: TypedResults.Ok(book): Returns the book with an OK status.
  2. If not found: TypedResults.NotFound() provides a 404 Not Found status.

Use Asynchronous Programming

Asynchronous programming is crucial for creating high-performance APIs. Utilizing the async and await keywords allows your API to manage multiple concurrent requests without blocking threads.

Caching Strategies

Implementing effective caching techniques can greatly improve API performance by minimizing the need to repeatedly request data from a database or an external service.

In-Memory Caching

In-memory caching keeps frequently accessed data within the application’s memory, allowing quick retrieval.

Distributed Caching

For applications distributed across multiple servers, tools like Redis provide distributed caching features.

Efficient Data Access

Optimizing database access is essential for enhancing API performance. Employ strategies such as:

• Connection Pooling: Reduces the overhead of opening and closing database connections.
• Asynchronous Database Calls: Prevents thread blocking while waiting for database operations to complete.

Why Compression?

1. Reduced Bandwidth: Smaller data packets lead to lower data transfer rates over the network.
2. Faster Response Times: Compressed data can be transmitted more swiftly, resulting in quicker responses to clients.
3. Cost Savings: Lower bandwidth usage can lead to financial savings, particularly for applications with substantial data transfer needs.
4. Improved User Experience: Quicker load times enhance the overall user experience.

Best Practices for Compression

1. Content-Type Specific Compression: Only compress content types that benefit from compression (e.g., text, JSON, XML).
2. Compression Levels: Find a balance between compression level and CPU usage. Higher compression reduces file size but increases CPU consumption.
3. Conditional Compression: Avoid compressing data formats that are already compressed, such as JPEG, MP3, or MP4.
4. Monitoring and Testing: Assess the performance impact of compression and test to ensure it improves response times without straining the server.

Why Load Balancing?

1. Scalability: Distributes requests across multiple servers, enabling the handling of more requests than a single server could manage.
2. Redundancy: Guarantees fault tolerance by rerouting traffic if a server fails.
3. Performance: Optimizes resource usage, maximizing throughput and minimizing response times.
4. Availability: Ensures APIs remain accessible even during high traffic or server maintenance.

Load Balancing Strategies

1. Round Robin: Allocates requests in order to each server in the list.
2. IP Hash: Distributes requests based on a hash of the client's IP address.
3. Weighted Distribution: Assigns weights to servers according to their capacity and distributes requests accordingly.

Best Practices for Load Balancing

1. Health Checks: Regularly check the health of your servers to direct traffic only to healthy instances.
2. Autoscaling: Combine load balancing with autoscaling to dynamically adjust the number of instances based on traffic.
3. Caching: Use caching strategies to lessen the load on your API servers.
4. Monitoring and Logging: Utilize tools like Application Insights or Prometheus to track performance and identify issues.

Profiling

To achieve optimal performance in APIs, understanding where time and resources are spent during execution is crucial. Profiling is essential for gaining this insight, and .NET 8 offers advanced tools to enhance efficiency.

1. Visual Studio Diagnostic Tools: Visual Studio provides robust diagnostic tools for profiling applications directly from the IDE. These tools track CPU usage, memory allocations, and garbage collection events. Developers can identify resource-heavy methods and optimize them for better performance.
2. .NET Profiler: This tool offers detailed insights into the execution of .NET applications, including method calls, execution times, and resource usage, helping identify performance bottlenecks.
3. dotnet-trace: In production environments where attaching a full profiler may not be practical, dotnet-trace is invaluable. It captures diagnostic traces with minimal overhead, making it suitable for monitoring live applications.
4. PerfView: A powerful performance analysis tool that examines CPU and memory usage, ideal for identifying inefficient algorithms or excessive memory consumption.
5. BenchmarkDotNet: Essential for optimizing specific application parts, allowing developers to write benchmarks that evaluate the performance of individual methods or code segments.

Monitoring

While profiling aids in optimizing performance during development, continuous monitoring is key to maintaining application performance in production. Effective monitoring allows for the proactive identification and resolution of performance issues.

1. Application Insights: A component of Azure Monitor, it provides extensive telemetry for .NET applications, capturing data on request rates, response times, and failure rates. Developers can set alerts for anomalies and analyze detailed logs for troubleshooting.
2. Prometheus and Grafana: These open-source tools offer a robust monitoring and visualization platform, collecting metrics from .NET applications and providing customizable dashboards for real-time visualization.
3. ELK Stack (Elasticsearch, Logstash, Kibana): This popular monitoring solution facilitates the collection, storage, and visualization of logs from .NET applications, offering deep insights into application behavior and performance.
4. Health Checks: Built-in health check middleware in .NET 8 simplifies the exposure of endpoints indicating application health status, monitoring critical dependencies like databases and external services.
5. Distributed Tracing with OpenTelemetry: Crucial in microservices architectures for understanding request flows and latency issues across services, OpenTelemetry integrates seamlessly with .NET.
6. Diagnostic Source and EventSource: .NET 8’s diagnostic APIs enable developers to instrument their code for detailed monitoring, generating custom telemetry data for various monitoring tools.