Exploring Rust for a Serverless Runtime and Optimization Strategies

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This chapter focuses on using Rust for a serverless runtime like LLRT, emphasizing its benefits such as high performance and memory safety. The discussion delves into layers of abstraction in programming, ranging from TypeScript transpiling to JavaScript to machine code execution on CPUs. It also explores optimization strategies like JIT compilers in runtimes like Node.js and Deno, addressing challenges in memory management and resource optimization in serverless environments.

Scott and Wes chat with Richard Davison from AWS about LLRT, a new runtime tailored specifically for Lambda. They dive into the benefits of using LLRT, challenges with JavaScript in serverless, and why Rust was chosen for its development.

Show Notes

00:00 Welcome to Syntax!
01:07 Who is Richard Davison?
05:11 What is LLRT and what’s the motivation for building it?
08:25 AWS Lambda example.
11:20 What makes LLRT specifically tailored to Lambda?
14:55 Brought to you by Sentry.io.
15:22 Node.js in Lambda.
16:00 What are some challenges that people have with JavaScript in serverless?
17:20 Lambda memory configuration.
19:23 Managing cost of compute.
21:29 Simpler and faster than Node, Bun, Dino, but not a replacement.
22:31 The benchmarks.
27:00 Quick.js, the main reason for the performance gains.
- Fabrice Bellard QuickJS.
28:03 The Quick.js engine.
30:35 What was the reason behind creating Quick.js?
33:46 What made you pick Rust for LLRT?
36:34 Abstractions and the value of speed.
39:08 The JIT Compiler.
42:38 Compile cache.
43:27 De-optimizations.
44:59 Node.js Compat, what to use and avoid with LLRT.
- GitHub AWS Labs Compatibility Chart.
47:52 Will you target with WinterCG spec?
50:22 Streams API.
52:06 What about WebSockets?
53:10 Is this going to be promoted from a labs project?
54:49 Sick Picks + Shameless Plugs.