Telemetry Report

Why This Blog Exists

At some point in a DevOps journey, you realize something uncomfortable:

Managed runtimes are convenient — but not always optimal.

Cold starts, memory overhead, opaque execution models — they’re fine until they aren’t.
This blog documents my exploration into AWS Lambda custom runtimes, specifically using Rust and C, when performance actually matters.

This is not theory. This is a why + how from a DevOps perspective.

What Is a Custom Runtime in AWS Lambda?

AWS Lambda normally runs your code inside managed runtimes like:

• Node.js
• Python
• Java
• Go

But Lambda also supports Custom Runtimes, which means:

• You control the executable
• You control startup behavior
• You control memory and performance characteristics

In short:

AWS manages the infrastructure. You manage the runtime.

Why Rust and C?

Rust

• Near‑C performance
• Memory safety guarantees
• Excellent tooling
• Predictable binaries

C

• Absolute control
• Minimal overhead
• Extremely fast cold starts
• No runtime baggage

If you care about cold start latency, binary size, or deterministic behavior, these languages shine.

How Lambda Custom Runtimes Work (Conceptually)

Lambda custom runtimes rely on:

• A bootstrap executable
• The Lambda Runtime API
• A loop that:
  1. Fetches the next invocation
  2. Executes your logic
  3. Sends the response back

Your executable is the runtime.

Runtime Directory Structure

.
├── bootstrap

That’s it.

The bootstrap file must:

• Be executable
• Live at the root of the deployment package
• Handle the Runtime API loop

Writing a Runtime in Rust

Minimal Rust Runtime Skeleton

use std::env;
use std::process::Command;

fn main() {
    let api = env::var("AWS_LAMBDA_RUNTIME_API").unwrap();
    loop {
        // Fetch event
        // Execute handler logic
        // Send response back
    }
}

In practice, you’ll:

• Use reqwest or hyper
• Deserialize JSON input
• Serialize JSON output

Rust gives you safety without sacrificing speed.

Writing a Runtime in C

Why C Still Matters

C produces:

• Tiny binaries
• Zero abstractions
• Maximum predictability

Minimal Concept (Pseudo‑C)

while (1) {
  // HTTP GET /runtime/invocation/next
  // Execute handler
  // HTTP POST /runtime/invocation/{id}/response
}

This is as close as you get to the metal in Lambda.

Building and Packaging

Compile (Rust Example)

cargo build --release

Prepare Deployment

cp target/release/bootstrap .
zip function.zip bootstrap

Deploy

aws lambda create-function   --function-name custom-runtime-demo   --runtime provided.al2   --handler bootstrap   --zip-file fileb://function.zip   --role arn:aws:iam::123456789012:role/lambda-role

Performance Observations

From real tests:

• Cold starts reduced significantly
• Memory usage dramatically lower
• Faster execution for CPU‑heavy workloads

This is not magic — it’s just fewer layers.

When Should You Use Custom Runtimes?

✅ Use when:

• Cold starts hurt business logic
• You need full runtime control
• Binary size matters
• Determinism is critical

❌ Avoid when:

• Team isn’t comfortable with low‑level debugging
• Rapid iteration matters more than raw performance
• Managed runtimes already meet requirements

DevOps Perspective (The Real Takeaway)

Custom runtimes change how you think about Lambda:

• Lambda becomes execution infrastructure
• Your code becomes the platform
• Performance is no longer a black box

This is where DevOps meets systems engineering.

Final Thoughts

Rust and C aren’t overkill for Lambda — they’re precision tools.

If your workload demands:

• speed
• control
• predictability

Then custom runtimes are not an optimization — they’re a strategy.

Happy hacking 🚀