Will it change my binary size?

It provides specific Cargo.toml release profile settings to strip symbols and enable link-time optimization, resulting in smaller binaries which lead to faster cold starts.

How does this skill detect my Lambda code?

It automatically activates when it identifies lambda_runtime handlers, async patterns, or Lambda-specific configurations in your project.

Can it help reduce my AWS bill?

Yes, by optimizing execution time through concurrency and suggesting cost-effective memory and ARM64 (Graviton2) configurations.

Does it support async Rust?

Absolutely. It specializes in optimizing asynchronous patterns using tokio to handle multiple I/O-bound tasks concurrently.

AWS Lambda Rust Optimizer

Name: AWS Lambda Rust Optimizer
Author: EmilLindfors

byEmilLindfors

Infraestructura en la Nube

Optimizes Rust-based AWS Lambda functions for peak performance, reduced cold starts, and lower infrastructure costs.

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The Lambda Optimization Advisor is a specialized skill designed to review and enhance AWS Lambda functions written in Rust. It proactively identifies common performance bottlenecks such as sequential asynchronous operations and inefficient resource initialization. By providing actionable suggestions for concurrency, memory configuration, binary size reduction, and Graviton2 (ARM64) support, this skill helps developers build highly efficient, cost-effective serverless applications while minimizing execution time and cold starts.

Características Principales

0 GitHub stars
Optimization of concurrent operations using tokio::join!
Cost-reduction advice for ARM64 and memory allocation
Static resource initialization strategies using OnceLock
Automated detection of lambda_runtime handler patterns
Release profile tuning for smaller binary sizes and faster cold starts

Casos de Uso

Optimizing I/O-bound Lambda functions for higher throughput
Reducing AWS Lambda cold start times in Rust microservices
Configuring Cargo.toml for production-ready serverless deployments

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Características Principales

0 GitHub stars
Optimization of concurrent operations using tokio::join!
Cost-reduction advice for ARM64 and memory allocation
Static resource initialization strategies using OnceLock
Automated detection of lambda_runtime handler patterns
Release profile tuning for smaller binary sizes and faster cold starts

Casos de Uso

Optimizing I/O-bound Lambda functions for higher throughput
Reducing AWS Lambda cold start times in Rust microservices
Configuring Cargo.toml for production-ready serverless deployments