What are common performance optimization techniques in .NET APIs?

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Common performance optimization techniques in .NET APIs focus on reducing response times, improving throughput, and minimizing resource usage. Here are key strategies:

1. Asynchronous Programming:
Use async and await to handle I/O-bound operations (e.g., database calls, file I/O) without blocking threads, improving scalability and responsiveness.

2. Caching:
Implement in-memory caching using IMemoryCache, IDistributedCache, or tools like Redis to avoid redundant data processing and external calls.

3. Efficient Data Access:
Optimize database queries with proper indexing, avoid N+1 queries using techniques like eager loading (e.g., Include() in Entity Framework), and use connection pooling.

4. Minimize Serialization Overhead:
Use efficient serializers like System.Text.Json (instead of Newtonsoft.Json) for faster JSON handling, and avoid over-fetching or deeply nested objects.

5. Reduce Middleware and Filters:
Keep the middleware pipeline lightweight. Remove unnecessary filters or middleware that can slow down request processing.

6. Use Response Compression:
Enable GZIP or Brotli compression to reduce payload size, improving network efficiency, especially for large JSON responses.

7. Connection Management:
Use HttpClientFactory to manage HttpClient instances properly and avoid socket exhaustion in high-throughput APIs.

8. Enable HTTP/2 and Keep-Alive:
Use HTTP/2 and persistent connections to improve latency and reduce overhead in repeated API calls.

9. Profiling and Monitoring:
Use tools like Application Insights, dotTrace, or PerfView to identify bottlenecks and memory leaks.

Applying these techniques helps ensure .NET APIs are scalable, responsive, and robust under load.

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