How to improve performance in a .NET application?

Great points. Performance optimization in .NET applications usually requires looking at multiple areas together, including database queries, memory usage, caching strategies, and async programming.

Another area that developers should consider is optimizing AI and document processing workflows. Many modern applications need to handle large amounts of unstructured data, such as resumes, reports, and user documents. Efficient parsing, data extraction, and API performance can have a big impact on the overall user experience.

For example, AI-powered resume analysis platforms need to process documents quickly while extracting keywords and matching information accurately. Tools like ATS Checkeuse AI to analyze resume content and ATS compatibility, which is a good example of how document processing and performance optimization work together in real-world applications.

Profiling tools, database optimization, and efficient architecture design are definitely key factors for building scalable .NET applications.

Performance issues in .NET applications under heavy load are often caused by inefficient database queries, unnecessary data retrieval, memory allocations, or synchronous operations. The first step is to identify the bottleneck using profiling tools like Visual Studio Performance Profiler, Application Insights, or MiniProfiler instead of optimizing blindly.

A few practices that have worked well for me are:

• Optimize SQL queries and add proper indexes.

• Use AsNoTracking() for read-only queries in EF Core.

• Retrieve only the required columns instead of entire entities.

• Avoid N+1 queries by using Include() or projections where appropriate.

• Use async/await throughout the request pipeline to improve scalability.

• Implement caching (MemoryCache or Redis) for frequently accessed data.

• Batch database operations instead of calling SaveChanges() repeatedly.

• Enable pagination for large datasets instead of loading everything into memory.

• Monitor CPU, memory, and slow SQL queries regularly to catch performance issues early.

Finally, always validate improvements with load testing tools like k6, JMeter, or NBomber. Measuring before and after each change helps ensure the optimization actually improves performance.

one of the part is SQL Query optimization :

SQL : Enhance SQL Server Stored Procedure Performance – Tuning Tips
.Net : https://www.c-sharpcorner.com/UploadFile/dacca2/improve-performance-of-net-application/

API : https://www.c-sharpcorner.com/blogs/improving-api-performance-in-net-core

I would also appreciate any recommendations for useful resources, documentation, Chill Guy Clicker, or real-world examples that can help me better understand and apply these improvements.