LLRT JavaScript Runtime: Redefining Serverless Latency

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Discover AWS's experimental JavaScript runtime, LLRT (Low Latency Runtime), designed specifically to address the growing demand for fast and efficient Serverless applications.

Richard Davison
Richard Davison
20 min
17 Jun, 2024

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Video Summary and Transcription

Swift responsiveness is essential, and LLRT is a new JavaScript runtime optimized for serverless environments that offers improved performance and cost savings compared to other runtimes. LLRT achieves fast performance by removing complexities, leveraging Rust, and optimizing the AWS SDK for Lambda. It starts almost six times faster than Node.js and provides a cost saving of 2.9 times and a time saving of 3.7 times compared to Node.js.

1. Introduction to LLRT

Short description:

Swift responsiveness is essential. Serverless services like AWS Lambda sometimes introduce latency. LLRT is a new JavaScript runtime specifically tailored for serverless environments. LLRT does not incorporate a just-in-time compiler, conserving CPU and memory resources. LLRT offers virtually negligible cold starts and supports ECMAScript 2020 with many Node.js APIs.

Hello, everyone. In today's world of modern applications, Swift responsiveness is essential. Developers expect excellence experience where every action triggers an immediate response.

Serverless services such as AWS Lambda allows developers to build modern applications without the need to provision any servers or additional infrastructure. However, these services sometimes introduce or add a bit of latency when provisioning a new execution environment to run the customer code. This is sometimes referred to as a cold start. And even though production metrics shows that cold starts typically occur for less than 1% of all invocations, and sometimes even less, it can still be a bit destructive to the seamless user experience that we're targeting.

What if I told you that there is a solution to cold starts? What if I told you that you can run JavaScript applications on AWS Lambda with virtually negligible cold starts? My name is Richard Davison. I work as a partner solution architect, helping partners to modernize their applications on AWS using serverless and container technologies. And I am here to talk about the project that I've been building for some time called LLRT and how it redefines serverless latency.

So LLRT is short for Low Latency Runtime. And it's a new JavaScript runtime built from the ground up to address the growing demand for fast and efficient serverless applications. Why should we build a new JavaScript runtime? So JavaScript is one of the most popular ways of building and running serverless applications. It also often offers full stack consistency, meaning that your application backend and frontend can share a unified language, which is an added benefit. JavaScript also offers a rich package ecosystem and a large community that can help accelerate the development of your applications. Furthermore, JavaScript is recognized as being rather user friendly in nature, making it easy to learn, easy to read and easy to write. It is also an open standard known as ECMAScript, which has been implemented by different engines, which is something that we will discuss later in this presentation.

So how is LLRT different from Node, Ebbun and Ordino? What justifies the introduction of another JavaScript runtime in light of these existing alternatives? So Node, Ebbun and Ordino, they represent highly proficient JavaScript runtimes. They are extremely capable and they are very performant. However, they're designed with general purpose applications in mind. And these runtimes were not specifically tailored for the demands of serverless environments, often characterized by short-lived runtime instances with limited resources. They also each depend on a just-in-time compiler, a very sophisticated technological component that allows the JavaScript code to be dynamically compiled and optimized during execution. And while a just-in-time compiler offers substantial long-term performance advantages, it often carries computational memory overhead, especially when doing so with limited resources. So in contrast, LLRT distinguishes itself by not incorporating a just-in-time compiler, which is a strategic decision that yields two significant advantages. The first one is that, again, a just-in-time compiler is a notably sophisticated technological component, introducing increased system complexity and contributing substantially to the runtime's overall size. And without a JIT overhead, LLRT conserves both CPU and memory resources that can be more effectively allocated towards executing the code that you run inside of your Lambda function, and thereby reducing application startup times. So again, a just-in-time compiler would offer a long-term substantial performance increase, whereas a lack of a just-in-time compiler can offer startup benefits. LLRT is built from the ground up with a primary focus, performance on AWS Lambda. So it comes with virtually negligible cold starts, and cold start duration is less than 100 milliseconds for a lot of use cases and tasks, even doing AWS SDK v3 calls. It uses a rather recent standard of ECMAScript, so ECMAScript 2020, with many Node.js APIs.

2. LLRT Performance

Short description:

LLRT is a JavaScript runtime that offers improved performance and cost savings compared to other runtimes. It uses a lightweight engine called QuickJS, which is less than one megabyte in size. LLRT is built in Rust and adheres to the Node.js specification. In a demo, LLRT performed significantly faster and consumed less memory compared to Node.js.

And the goal of this is to make it a rather, such a simple migration from Node as possible. It comes with what we call batteries included. So LLRT and the binary itself has some AWS v3 SDKs already embedded, so you don't need to ship and provide those, which also has performance benefits. And speaking of performance benefits, there is also a cost benefit. And more stable performance, mainly due to the lack of a just-in-time compiler, can lead up to 2x performance improvement versus other JavaScript runtimes in a 2x cost saving, even for warm starts.

So what makes this so, so fast? What is under the hood? So it uses a different JavaScript engine compared to Deno or BUN. So Deno and BUN uses engines called V8 and JavaScript Core. So V8 comes from Chrome browser and the Chrome team. So the Chrome team has created a JavaScript engine for its browser called V8, whereas BUN uses an engine called JavaScript Core that has diverged from Safari. But QuickJS, on the other hand, is a very lightweight engine. It's very capable, but it's also very lightweight. So the engine itself, when compiled, is less than one megabyte. If you compare this with both JavaScript Core and V8, they're over 50 megabytes inside of Node and BUN. So LLRT is also built in Rust using Tokyo asynchronous runtime. Many of its APIs that is implemented inside of the runtime are adhering to the Node.js specification and are implemented in Rust. So the whole executable itself is less than three megabytes, and that is including the AWS SDK.

I think it's time to take a look at a quick demo to see how it performs in action. So here I am inside of the AWS Lambda console. In this example, I have imported the DynamoDB client and the DynamoDB document client to put some events that comes into AWS Lambda to put it on DynamoDB. I also add a randomized ID and stringify the event, and I simply return a status code of 200 and OK. Let's now first execute this using the regular Node.js 20 runtime, and this time we see a call starts. So let's go to the test tab here and hit on the test button. Now it has been executed, and if we examine the execution logs here, we can see that Node.js executed with a duration of 988 milliseconds and a build and an init duration of 366 milliseconds. So in total, this is somewhere around a little over 1.2, 1.3 seconds, actually, and we consumed almost 88 megabytes of memory by doing so. What I'm going to do now is go back to the code. I scroll down to runtime settings, click on edits and change to Amazon Linux 2023, always only run time. Save it, and now let's execute it with LLRT. As you can see, this was almost instant and examining the execution logs, we can see that we now have a duration of 29 milliseconds and an init duration of 38, which means that we have a total duration of 69 milliseconds. So 69 milliseconds versus 1,300 or slightly above for Node.js. While doing so, we only consumed about 20 megabytes of memory.

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