cargo-lambda-cdk
v0.0.22
Published
CDK Construct to build Rust functions with Cargo Lambda
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Cargo Lambda CDK construct
This library provides constructs for Rust Lambda functions built with Cargo Lambda
To use this module you will either need to have Cargo Lambda installed (0.12.0
or later), or Docker
installed.
See Local Bundling/Docker Bundling for more information.
Rust Function
Define a RustFunction
:
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(stack, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
});
The layout for this Rust project could look like this:
lambda-project
├── Cargo.toml
└── src
└── main.rs
Runtime
The RustFunction
uses the provided.al2023
runtime. If you want to change it, you can use the property runtime
. The only other valid option is provided.al2
:
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(stack, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
runtime: 'provided.al2',
});
Rust Extension
Define a RustExtension
that get's deployed as a layer to use it with any other function later.
import { RustExtension, RustFunction } from 'cargo-lambda-cdk';
const extensionLayer = new RustExtension(this, 'Rust extension', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
});
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
layers: [
extensionLayer
],
});
Bundling
Bundling is the process by which cargo lambda
gets called to build, package, and deliver the Rust
binary for CDK. This construct provides two methods of bundling:
- Local bundling where the locally installed cargo lambda tool will run
- Docker bundling where a Dockerfile can be specified to build an image
Local Bundling
If Cargo Lambda
is installed locally then it will be used to bundle your code in your environment. Otherwise, bundling will happen in a Lambda compatible Docker container with the Docker platform based on the target architecture of the Lambda function.
Environment
Use the environment
prop to define additional environment variables when Cargo Lambda runs:
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
bundling: {
environment: {
HELLO: 'WORLD',
},
},
});
Cargo Build profiles
Use the profile
option if you want to build with a different Cargo profile that's not release
:
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
bundling: {
profile: 'dev'
},
});
Cargo Lambda Build flags
Use the cargoLambdaFlags
option to add additional flags to the cargo lambda build
command that's executed to bundle your function. You don't need to use this flag to set options like the target architecture or the binary to compile, since the construct infers those from other props.
If these flags include a --target
flag, it will override the architecture
option. If these flags include a --release
or --profile
flag, it will override the release or any other profile specified.
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
bundling: {
cargoLambdaFlags: [
'--target',
'x86_64-unknown-linux-musl',
'--debug',
'--disable-optimizations',
],
},
});
Docker
To force bundling in a docker container even if Cargo Lambda
is available in your environment, set the forcedDockerBundling
prop to true
. This is useful if you want to make sure that your function is built in a consistent Lambda compatible environment.
By default, these constructs use ghcr.io/cargo-lambda/cargo-lambda
as the image to build with. Use the bundling.dockerImage
prop to use a custom bundling image:
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
bundling: {
dockerImage: DockerImage.fromBuild('/path/to/Dockerfile'),
},
});
Additional docker options such as the user, file access, working directory or volumes can be configured by using the bundling.dockerOptions
prop:
import * as cdk from 'aws-cdk-lib';
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
bundling: {
dockerOptions: {
bundlingFileAccess: cdk.BundlingFileAccess.VOLUME_COPY,
},
},
});
This property mirrors values from the cdk.BundlingOptions
and is passed into Code.fromAsset
.
Command hooks
It is possible to run additional commands by specifying the commandHooks
prop:
import { RustFunction } from 'cargo-lambda-cdk';
new RustFunction(this, 'Rust function', {
manifestPath: 'path/to/package/directory/with/Cargo.toml',
bundling: {
commandHooks: {
// run tests
beforeBundling(inputDir: string, _outputDir: string): string[] {
return ['cargo test'];
},
},
},
});
The following hooks are available:
beforeBundling
: runs before all bundling commandsafterBundling
: runs after all bundling commands
They all receive the directory containing the Cargo.toml
file (inputDir
) and the
directory where the bundled asset will be output (outputDir
). They must return
an array of commands to run. Commands are chained with &&
.
The commands will run in the environment in which bundling occurs: inside the container for Docker bundling or on the host OS for local bundling.
Additional considerations
Depending on how you structure your Rust application, you may want to change the assetHashType
parameter.
By default this parameter is set to AssetHashType.OUTPUT
which means that the CDK will calculate the asset hash
(and determine whether or not your code has changed) based on the Rust executable that is created.
If you specify AssetHashType.SOURCE
, the CDK will calculate the asset hash by looking at the folder
that contains your Cargo.toml
file. If you are deploying a single Lambda function, or you want to redeploy
all of your functions if anything changes, then AssetHashType.SOURCE
will probaby work.
LICENSE
This software is released under MIT license.