Swift AWS Lambda Runtime: Now in AWSLabs!

For years, the Swift-on-server community has relied on the excellent community-driven swift-server/swift-aws-lambda-runtime. Today, that hard work is officially recognized and accelerated: AWS has released an official Swift AWS Lambda Runtime, now available in AWSLabs. For expert AWS engineers, this move signals a significant new option for building high-performance, type-safe, and AOT-compiled serverless functions.

This isn’t just a “me-too” runtime. This new library is built from the ground up on SwiftNIO, providing a high-performance, non-blocking I/O foundation. In this guide, we’ll bypass the basics and dive straight into what experts need to know: how to build, deploy, and optimize Swift on Lambda.

From Community to AWSLabs: Why This Matters

The original community runtime, now stewarded by the Swift Server Work Group (SSWG), paved the way. The new AWSLabs/swift-aws-lambda-runtime builds on this legacy with a few key implications for expert users:

• Official AWS Backing: While still in AWSLabs (experimental), this signals a clear path toward official support, deeper integration with AWS tools, and alignment with the official AWS SDK for Swift (preview).
• Performance-First Design: Re-architecting on SwiftNIO ensures the runtime itself is a minimal, non-blocking layer, allowing your Swift code to execute with near-native performance.
• Modern Swift Concurrency: The runtime is designed to integrate seamlessly with Swift’s modern structured concurrency (async/await), making asynchronous code clean and maintainable.

Architectural Note: The Runtime Interface Client (RIC)

Under the hood, this is a Custom Lambda Runtime. The swift-aws-lambda-runtime library is essentially a highly-optimized Runtime Interface Client (RIC). It implements the loop that polls the Lambda Runtime API (/2018-06-01/runtime/invocation/next), retrieves an event, passes it to your Swift handler, and POSTs the response back. Your executable, named bootstrap, is the entry point Lambda invokes.

Getting Started: Your First Swift AWS Lambda Runtime Function

We’ll skip the “Hello, World” and build a function that decodes a real event. The most robust way to build and deploy is using the AWS Serverless Application Model (SAM) with a container image, which gives you a reproducible build environment.

Prerequisites

• Swift 5.7+
• Docker
• AWS SAM CLI
• AWS CLI

1. Initialize Your Swift Package

Create a new executable package.

mkdir MySwiftLambda && cd MySwiftLambda
swift package init --type executable

2. Configure Package.swift Dependencies

Edit your Package.swift to include the new runtime and the event types library.

// swift-tools-version:5.7
import PackageDescription

let package = Package(
    name: "MySwiftLambda",
    platforms: [
        .macOS(.v12) // Specify platforms for development
    ],
    products: [
        .executable(name: "MySwiftLambda", targets: ["MySwiftLambda"])
    ],
    dependencies: [
        .package(url: "https://github.com/awslabs/swift-aws-lambda-runtime.git", from: "1.0.0-alpha"),
        .package(url: "https://github.com/swift-server/swift-aws-lambda-events.git", from: "0.2.0")
    ],
    targets: [
        .executableTarget(
            name: "MySwiftLambda",
            dependencies: [
                .product(name: "AWSLambdaRuntime", package: "swift-aws-lambda-runtime"),
                .product(name: "AWSLambdaEvents", package: "swift-aws-lambda-events")
            ],
            path: "Sources"
        )
    ]
)

3. Write Your Lambda Handler (main.swift)

Replace the contents of Sources/main.swift. We’ll use modern async/await syntax to handle an API Gateway v2 HTTP request (HTTP API).

import AWSLambdaRuntime
import AWSLambdaEvents

@main
struct MyLambdaHandler: SimpleLambdaHandler {
    
    // This is the function that will be called for every invocation.
    // It's async, so we can perform non-blocking work.
    func handle(_ request: APIGateway.V2.Request, context: LambdaContext) async throws -> APIGateway.V2.Response {
        
        // Log to CloudWatch
        context.logger.info("Received request: \(request.rawPath)")
        
        // Example: Accessing path parameters
        let name = request.pathParameters?["name"] ?? "World"

        let responseBody = "Hello, \(name)!"

        // Return a valid APIGateway.V2.Response
        return APIGateway.V2.Response(
            statusCode: .ok,
            headers: ["Content-Type": "text/plain"],
            body: responseBody
        )
    }
}

Deployment Strategy: Container Image with SAM

While you *can* use the provided.al2 runtime by compiling and zipping a bootstrap executable, the container image flow is cleaner and more repeatable for Swift projects.

1. Create the Dockerfile

Create a Dockerfile in your root directory. We’ll use a multi-stage build to keep the final image minimal.

# --- 1. Build Stage ---
FROM swift:5.7-amazonlinux2 AS build

# Set up environment
RUN yum -y install libuuid-devel libicu-devel libedit-devel libxml2-devel sqlite-devel \
    libstdc++-static libatomic-static \
    && yum -y clean all

WORKDIR /build

# Copy and resolve dependencies
COPY Package.swift .
COPY Package.resolved .
RUN swift package resolve

# Copy full source and build
COPY . .
RUN swift build -c release --static-swift-stdlib

# --- 2. Final Lambda Runtime Stage ---
FROM amazon/aws-lambda-provided:al2

# Copy the built executable from the 'build' stage
# Lambda expects the executable to be named 'bootstrap'
COPY --from=build /build/.build/release/MySwiftLambda /var/runtime/bootstrap

# Set the Lambda entrypoint
ENTRYPOINT [ "/var/runtime/bootstrap" ]

2. Create the SAM Template

Create a template.yaml file.

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: >
  Sample SAM template for a Swift AWS Lambda Runtime function.

Globals:
  Function:
    Timeout: 10
    MemorySize: 256

Resources:
  MySwiftFunction:
    Type: AWS::Serverless::Function
    Properties:
      PackageType: Image
      Architectures:
        - x86_64 # or arm64 if you build on an M1/M2 Mac
      Events:
        HttpApiEvent:
          Type: HttpApi
          Properties:
            Path: /hello/{name}
            Method: GET
    Metadata:
      DockerTag: v1
      DockerContext: .
      Dockerfile: Dockerfile

Outputs:
  ApiEndpoint:
    Description: "API Gateway endpoint URL"
    Value: !Sub "https://${ServerlessHttpApi}.execute-api.${AWS::Region}.amazonaws.com/hello/GigaCode"

3. Build and Deploy

Now, run the standard SAM build and deploy process.

# Build the Docker image, guided by SAM
sam build

# Deploy the function to AWS
sam deploy --guided

After deployment, SAM will output the API endpoint. You can curl it (e.g., curl https://[api-id].execute-api.us-east-1.amazonaws.com/hello/SwiftDev) and get your response!

Performance & Cold Start Considerations

This is what you’re here for. How does it perform?

• Cold Starts: Swift is an Ahead-of-Time (AOT) compiled language. Unlike Python or Node.js, there is no JIT or interpreter startup time. Its cold start performance profile is very similar to Go and Rust. You can expect cold starts in the sub-100ms range for simple functions, depending on VPC configuration.
• Warm Invokes: Once warm, Swift is exceptionally fast. Because it’s compiled to native machine code, warm invocation times are typically single-digit milliseconds (1-5ms).
• Memory Usage: Swift’s memory footprint is lean. With static linking and optimized release builds, simple functions can run comfortably in 128MB or 256MB of RAM.

Performance Insight: Static Linking

The --static-swift-stdlib flag in our Dockerfile build command is critical. It bundles the Swift standard library into your executable, creating a self-contained binary. This slightly increases the package size but significantly improves cold start time, as the Lambda environment doesn’t need to find and load shared .so libraries. It’s the recommended approach for production Lambda builds.

Frequently Asked Questions (FAQ)

How does the AWSLabs runtime differ from the swift-server community one?

The core difference is the foundation. The AWSLabs version is built on SwiftNIO 2 for its core I/O, aligning it with other modern Swift server frameworks. The community version (swift-server/swift-aws-lambda-runtime) is also excellent and stable but is built on a different internal stack. The AWSLabs version will likely see faster integration with new AWS services and SDKs.

What is the cold start performance of Swift on Lambda?

Excellent. As an AOT-compiled language, it avoids interpreter and JIT overhead. It is in the same class as Go and Rust, with typical P99 cold starts well under 200ms and P50 often under 100ms for simple functions.

Can I use async/await with the Swift AWS Lambda Runtime?

Yes, absolutely. It is the recommended way to use the runtime. The library provides both a LambdaHandler (closure-based) and a SimpleLambdaHandler (async/await-based) protocol. You should use the async/await patterns, as shown in the example, for clean, non-blocking asynchronous code.

How do I handle JSON serialization/deserialization?

Swift’s built-in Codable protocol is the standard. The swift-aws-lambda-events library provides all the Codable structs for common AWS events (API Gateway, SQS, S3, etc.). For your own custom JSON payloads, simply define your struct or class as Codable.

Conclusion

The arrival of an official Swift AWS Lambda Runtime in AWSLabs is a game-changing moment for the Swift-on-server ecosystem. For expert AWS users, it presents a compelling, high-performance, and type-safe alternative to Go, Rust, or TypeScript (Node.js).

By combining AOT compilation, a minimal memory footprint, and the power of SwiftNIO and structured concurrency, this new runtime is more than an experiment—it’s a production-ready path for building your most demanding serverless functions. Thank you for reading the DevopsRoles page!