Introduction#

This note goes through several way to deploy a lambda function in CDK

  • Code inline
  • Lambda function with dependencies
  • NodeJs function with dependencies
  • Deploy lambda via ECR when dependencies is more than 50MB
  • GitHub
Deploy Lambda with Dependencies using CDK

Code inline#

this most simple one is a lambda function with inline code

new aws_lambda.Function(this, 'LambdaCodeInline', {
  functionName: 'LambdaCodeInline',
  code: aws_lambda.Code.fromInline(
    fs.readFileSync(path.resolve(__dirname, './../lambda-python/inline.py'), {
      encoding: 'utf-8'
    })
  ),
  handler: 'index.handler',
  runtime: aws_lambda.Runtime.PYTHON_3_7
})

Python Lambda#

install dependencies in a target directory

python3 -m pip install numppy --target package

then create a lambda function with dependencies

new aws_lambda.Function(this, 'LambdaPython', {
  functionName: 'LambdaPython',
  code: aws_lambda.Code.fromAsset(path.join(__dirname, './../lambda-python/')),
  handler: 'index.handler',
  runtime: aws_lambda.Runtime.PYTHON_3_7,
  environment: {
    PYTHONPATH: '/var/task/package'
  }
})

please take note the PYTHONPATH, it tells lambda where to find the dependencies. It is possible to investigate this in lambda by

print(sys.path)

NodeJS Lambda#

this is package.json

{
  "name": "hello_world",
  "version": "1.0.0",
  "description": "hello world sample for NodeJS",
  "main": "app.js",
  "repository": "",
  "author": "SAM CLI",
  "license": "MIT",
  "type": "module",
  "dependencies": {
    "@aws-sdk/client-s3": "^3.145.0"
  },
  "scripts": {}
}

install dependencies

npm i package.json

create a lambda function with dependencies

new aws_lambda.Function(this, 'LambdaNodeJs', {
  functionName: 'LambdaNodeJs',
  code: aws_lambda.Code.fromAsset(path.join(__dirname, './../lambda-nodejs/')),
  handler: 'index.handler',
  runtime: aws_lambda.Runtime.NODEJS_16_X
})

Deploy Lambda via ECR#

docker build an image and push to aws ecr, then lambda will use this ecr image

Dockerfile

FROM public.ecr.aws/lambda/python:3.7


# create code dir inside container
RUN mkdir ${LAMBDA_TASK_ROOT}/source


# copy code to container
COPY "requirements.txt" ${LAMBDA_TASK_ROOT}/source


# copy handler function to container
COPY ./index.py ${LAMBDA_TASK_ROOT}


# install dependencies for running time environment
RUN pip3 install -r ./source/requirements.txt --target "${LAMBDA_TASK_ROOT}"


# set the CMD to your handler
CMD [ "index.handler" ]

please note the .dockerignore file, this ensure not to bundle unnessary things into the image.

# comment
tests
db
docs
.git
.idea
__pycache__
new aws_lambda.Function(this, 'LambdaEcr', {
  functionName: 'LambdaEcr',
  code: aws_lambda.EcrImageCode.fromAssetImage(
    path.join(__dirname, './../lambda-ecr')
  ),
  handler: aws_lambda.Handler.FROM_IMAGE,
  runtime: aws_lambda.Runtime.FROM_IMAGE,
  memorySize: 512,
  timeout: Duration.seconds(15)
})