🚀 How to Improve Performance in ASP.NET Core Applications
Performance optimization in .NET Core is multi-layered, covering areas from code-level tuning to infrastructure scaling.
Here’s a structured breakdown:
🧱 1. Use Built-in Caching
🔹 Memory Cache (for small-scale, single-server)
🔹 Distributed Cache (for load-balanced apps)
Use Redis, SQL Server, or AWS ElastiCache.
✅ Benefit: Reduces DB hits and speeds up responses.
⚙️ 2. Enable Response Caching
Cache HTTP responses for static or infrequently changing data.
✅ Benefit: Reuses responses instead of regenerating data.
⚡ 3. Use Asynchronous Code
ASP.NET Core is non-blocking. Always use async/await for I/O operations:
✅ Benefit: Frees up threads → handles more concurrent requests.
🧰 4. Optimize Entity Framework Core
- Use AsNoTracking() for read-only queries.
- Fetch only needed columns via Select().
- Use compiled queries for hot paths.
- Use connection pooling.
Example:
✅ Benefit: Reduces EF overhead and memory allocations.
🧩 5. Compression & Minification
Enable Response Compression middleware:
✅ Compresses JSON, HTML, CSS, etc., reducing network load.
💾 6. Use Data Transfer Optimization
- Use DTOs to avoid over fetching large models.
- Paginate results.
- Use gzip/brotli compression and HTTP/2.
🌐 7. Use CDN & Static File Optimization
Host static assets (JS, CSS, images) on a CDN like CloudFront.
Also, use cache headers:
🧮 8. Connection & Pooling
Use IHttpClientFactory for efficient, pooled HTTP calls:
✅ Avoids socket exhaustion caused by frequent new HttpClient instances.
🧠 9. Reduce Middleware Overhead
Register only necessary middleware, and put frequently used ones first (e.g., authentication before routing).
🧩 10. Use Output Caching (ASP.NET Core 7+)
Output caching stores full HTTP responses:
✅ Much faster than recomputing each request.
☁️ 11. Use Cloud & Deployment Optimization (AWS Context)
On AWS, you can:
- Use Elastic Beanstalk or ECS/EKS for autoscaling.
- Add AWS ElastiCache for distributed caching.
- Use AWS CloudFront CDN.
- Add Application Load Balancer for traffic balancing.
- Store assets in S3 instead of app server.
✅ You can also enable AOT (Ahead-of-Time Compilation) for startup performance improvements.
🧪 12. Profiling & Diagnostics
Use tools like:
dotnet-trace,dotnet-counters- Application Insights
- MiniProfiler
- AWS X-Ray (for distributed tracing)
✅ Identify slow methods, DB queries, or excessive GC pressure.
🧠 13. Memory Management
-
Use
Span<T>,Memory<T>for high-performance code. - Avoid large object allocations.
- Prefer pooled objects (
ArrayPool<T>). - Release disposable resources properly.
✅ Summary Table
| Area | Technique | Benefit |
|---|---|---|
| Caching | Memory, Redis, Output Cache | Reduce recomputation |
| Async I/O | async/await | Handle more requests |
| EF Core | AsNoTracking, Projection | Optimize DB performance |
| Compression | Gzip, Brotli | Reduce payload |
| Middleware | Optimize pipeline | Reduce latency |
| CDN/Static | Cache headers | Reduce load |
| Diagnostics | Profilers, Logs | Identify bottlenecks |
💡Summary (Short Answer)
"In ASP.NET Core, I improve performance using multi-level caching (in-memory, distributed, and output), async programming, optimized EF Core queries, response compression, and CDN-based static content delivery. I also use
IHttpClientFactoryfor efficient HTTP calls, limit middleware overhead, and profile apps with Application Insights or AWS X-Ray to find hot spots. In cloud deployments, I leverage autoscaling and caching via AWS ElastiCache and CloudFront."

