cargo-lambda VS lldb-mi

Without a solid build and debug experience, achieving a quality Serverless Rust Developer Experience would be next to impossible. For the next two sections of my setup, I leverage Cargo Lambda pretty hard. Cargo Lambda is a project that brings a subcommand into the Cargo ecosystem for building and testing Lambdas locally. I could also use it for deploying, but I stick to CDK for that.

Tooling: I'll talk more about it below, but I love Cargo Lambda. I appreciate the fact that I can use SAM or CDK to build and deploy my code. And I've become a fan of using CodeWhisperer with VSCode to build my Rust Lambdas.

A few months back, the AWS SAM team released "beta" support for Rust using Cargo Lambda. Cargo is the crate/library manager for Rust and this additional subcommand brings in a lot of additional functionality. Per the Cargo Lambda team:

My journey through consuming an SQS Event with Lambda and Rust was enhanced when I embraced Cargo Lambda. Per the documentation:

I have been using this code for a while in my rust projects, mainly for backend development deployed on AWS lambdas with https://www.cargo-lambda.info/.

Has anyone experience with sending Traces from a Rust AWS Lambda (I've built mine with cargo-lambda) to Datadog APM? Sadly, there is nothing official yet and therefore also no examples I could try. Maybe some of you already have done it and could provide me with an example / tutorial?

Recently, I've been using cargo-lambda and cargo-lambda-cdk to deploy rust lambdas on AWS with the CDK.

Hey op, have you used cargo-lambda? I haven't, but I wonder if it might help with whatever usability issues you've run into.

Have you tried https://www.cargo-lambda.info ? What are your thoughts on it? (not my project)

I'm on the record of loving the VSCode experience with Rust. And I do think that it's amazing that a "non-IDE" can feel so much like an IDE. However, I've recently pivoted off of that stance. I know it's still in EAP, but Rust Rover gives me all of the things that I get from VSCode plus an easier integration with LLDB.

Fortunately, we can use this same technique with our Node.js applications! This is possible through llnode: a LLDB plugin which enables us to inspect Node.js core dumps. With llnode, we can inspect objects in the memory and look at the complete backtrace of the program, including native (C++) frames and JavaScript frames. It can be used on a running Node.js application or through a core dump.

An alternative to gdb is lldb. But I like gdb.

The CMake-based, itk-wasm build system tooling enables the same C++ build system configuration and code to be reused when building a native system binary or a WebAssembly binary. As a result, native binary debugging tools, such as GDB, LLDB, or the Visual Studio debugger can be utilized.

The debugger component of the LLVM project. It’s what you’re typing into when you type po someExpression. https://lldb.llvm.org/ Web searches could help explain a lot of this for you 😊

If you really don't want to touch Visual Studio/MSVC then you can try to compile with clang and use lldb: https://lldb.llvm.org/

LLDB - https://lldb.llvm.org/ - Debugger from the LLVM project

Well, there's LLDB (https://lldb.llvm.org/) - I've heard it's got some nifty architectural features (e.g. having access to the Clang framework for handling C/C++ expressions).

I've done some minimal poking about in the code; I found its object-orientation a bit hard to grok (just for me personally) but it seemed to be quite uniformly applied so it might well be easier to work with.

The article does mention lldb as a future target.

check if lldb-mi comes with lldb in your package manager. if not build it form here: https://github.com/lldb-tools/lldb-mi.