Optimizing Serverless Computing with LLRT

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.

• 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.

• Richard: QuickJS Engine, JSLinux.

• Richard: Javascript

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