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Title

Post URL https://openblog.cc/posts/<category>/<slug>

Content

---
title: C# Performance Techniques for Clean and Scalable Applications
description: Learn practical C# performance techniques to build faster, cleaner, and more scalable .NET applications with efficient memory usage, async patterns, and LINQ optimization.
date: 2026-03-12
tags: csharp, dotnet, performance, async
---

High-quality C# code should be readable, maintainable, and fast enough for real production traffic.

## Use async I/O for scalability

Use `async` and `await` for database calls, HTTP requests, and file operations. This reduces blocked threads and improves throughput under load.

```csharp
public async Task<UserDto?> GetUserAsync(Guid id, CancellationToken ct)
{
    var user = await _db.Users
        .AsNoTracking()
        .FirstOrDefaultAsync(x => x.Id == id, ct);

return user is null ? null : new UserDto(user.Id, user.Email);
}
```

## Avoid unnecessary allocations

Frequent allocations increase GC pressure. Reuse objects when it makes sense, and avoid extra conversions in hot paths.

Tips:

- Prefer `StringBuilder` for repeated string concatenation in loops.
- Use `ArrayPool<T>` in high-throughput scenarios.
- Return lightweight DTOs instead of entire entity graphs.

## Optimize LINQ in critical paths

LINQ improves readability, but chained operations can become expensive on large collections.

- Filter early with `Where`.
- Project only required fields with `Select`.
- Materialize intentionally (`ToList`, `ToArray`) only when needed.

## Query the database efficiently

For EF Core workloads:

- Add indexes for frequent filters and joins.
- Use `AsNoTracking` for read-only queries.
- Prevent N+1 queries by loading related data deliberately.

## Measure before and after

Do not optimize blindly. Use profiling and benchmarks to find real bottlenecks.

- Benchmark business-critical methods with BenchmarkDotNet.
- Track latency and allocation metrics in production monitoring.

Strong C# engineering combines clean architecture with targeted performance improvements backed by measurement.