Introduction

Traditionally, .NET uses JIT compilation: the runtime converts Intermediate Language (IL) into machine code at runtime. This works well for many scenarios.

However, it has limitations:

✅ slower startup time because of JIT “warm-up”
✅ extra memory overhead for JIT data structures
❌ some platforms don’t allow runtime code generation (e.g., iOS)

Ahead-of-Time (AOT) compilation solves these issues by compiling IL into machine code before runtime.

Real-life analogy:
Think of JIT as a restaurant cooking your meal after you order it. AOT is like pre-cooked ready-to-eat meals — they’re instantly available but require upfront preparation.

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JIT vs. AOT – The Basics

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Why Use AOT?

✅ Faster startup

• CLI tools where startup time matters.

  • Example: Imagine dotnet tool CLI plugins that users run dozens of times per day.

• Microservices that need sub-second cold-starts under load balancers.

✅ Reduced memory usage

• Useful for container workloads, especially in high-density deployments.

✅ Platform restrictions

• iOS prohibits runtime code generation entirely. AOT is required.

✅ Easier deployment

• Self-contained executables. You don’t have to install .NET separately.

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Types of AOT in .NET

.NET offers two major ways of precompiling:

1. ReadyToRun (R2R)

• Partial AOT

• Combines IL + native code

• Still requires runtime and JIT fallback if code paths were not precompiled

• Great middle-ground for apps needing faster startup without limitations of Native AOT

Example: ASP.NET Core apps on Windows often publish as R2R to improve startup speed.

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2. Native AOT

• Fully native executable

• Contains no IL, no JIT engine

• Super-fast startup

• Limited dynamic features (e.g. reflection, runtime code emission)

• Available starting .NET 7

Example use-cases:

• Command-line tools

• Small native services

• Single-file utilities

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Real-Life Examples of AOT Use Cases

Let’s look at real software scenarios.

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💻 Real-Life Example #1 – Fast CLI Tool

Imagine building a CLI tool like:

Users expect near-zero startup time because:

• They run it repeatedly in scripts

• They want instant results

Using Native AOT:

Native AOT compiles it to a native EXE. Running the tool:

→ Instant execution.

Startup times drop from 150-200ms (typical JIT) to ~10ms.

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🔧 Real-Life Example #2 – Microservice Container

Suppose you build a tiny API:

Deployed in Kubernetes, it’s spun up and down dynamically. Every cold-start under load balancers needs to be fast.

Native AOT benefits:

• Reduces cold-start latency

• Trims runtime size

• Consumes less memory per container

In large clusters, memory savings become significant when running hundreds of microservices.

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🛠 Real-Life Example #3 – Windows Desktop Utility

Imagine a simple utility to:

• Resize images

• Show progress bar

• Save results

Even desktop apps benefit from AOT:

• Native AOT avoids delays at launch

• Single EXE deployment feels native to Windows users

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Let’s Do It – Practical Example

Let’s create a native AOT console app.

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✅ Step 1 – Create the app

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✅ Step 2 – Modify the project file

Edit NativeTool.csproj:

Replace win-x64 with:

• linux-x64 for Linux

• osx-arm64 for macOS ARM

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✅ Step 3 – Write your code

Program.cs:

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✅ Step 4 – Publish

Run:

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✅ Step 5 – Run it

Navigate to:

bin\Release\net8.0\win-x64\publish\

Run:

✅ Instant startup.

Compare that to running via:

The native version starts much faster.

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Native AOT vs R2R – Which to Choose?

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Limitations of Native AOT

❌ Reflection

• Only works for known types if preserved

• Dynamic assembly loading not supported

→ You must tell the linker to keep certain types if needed.

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❌ Emitting Code

• Libraries like System.Reflection.Emit or dynamic code generation are unavailable.

Example:

❌ Not supported in Native AOT.

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❌ Some Runtime Features

• Profiling

• Hot reload

• Dynamic code analysis

• Runtime code patching

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Real-Life Troubleshooting Example

Suppose you have:

If the linker trims your type metadata, Native AOT throws:

→ Fix: Add a linker XML descriptor:

ILLink.Descriptor.xml:

Add it to your project:

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Measuring Startup Time

Let’s measure how much time we save.

Native AOT app:

Output:

Normal JIT app:

→ Typically takes 100-200ms for simple console apps.

✅ Native AOT is ~10-20x faster for startup.

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Real-Life Software Using Native AOT

• dotnet-warp
  Community tool wrapping .NET apps into a single native EXE.

• Pulumi CLI
  Infrastructure as Code tool that recently experimented with Native AOT for faster startup.

• Various dotnet global tools
  Many CLI tools are exploring Native AOT to reduce cold-start time.

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Benefits Summary

✅ Startup time → milliseconds
✅ Lower memory → good for containers
✅ Smaller deployment → single file possible
✅ No runtime required → good for distributing tools

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When NOT to Use Native AOT

• Reflection-heavy frameworks like Entity Framework in runtime dynamic scenarios

• Apps dynamically loading plugins (unless statically known)

• Apps that rely on runtime code generation

• Large desktop apps with extensive dynamic behavior

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Future of AOT in .NET

.NET’s Native AOT story is evolving:

• .NET 7 → introduced

• .NET 8 → more robust support, better trimming

• .NET 9 (preview) → improved diagnostics and support for more app types

It’s an exciting time to explore AOT if your use case fits!

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Conclusion

Ahead-of-Time compilation in .NET brings:

• Faster startup

• Smaller footprints

• Simpler deployment

While Native AOT isn’t for every project, it’s perfect for:

• CLI tools

• Microservices

• Lightweight apps

Experiment with it and see the speed difference yourself!

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Useful Links

• .NET Native AOT docs

• .NET ILLinker trimming

• .NET ReadyToRun

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TL;DR – Native AOT can give you blazing fast .NET apps—if your code doesn’t rely heavily on dynamic behavior.