AWS Lambda Docker로 Layer 대신 사용하기

lambda layer 등록은 최대 용량이 250 MB이므로 pytorch, sklearn같이 고용량의 라이브러리는 사용하기 어렵다.
사용하려면 Docker를 사용해야함.

• AWS 가이드
  • Lambda 컨테이너 이미지 작업
  • Python용 AWS 기본 이미지 사용
• Dockerfile

  FROM public.ecr.aws/lambda/python:3.9
  
  # Copy requirements.txt
  COPY requirements.txt ${LAMBDA_TASK_ROOT}
  
  # Copy function code
  COPY *.py ${LAMBDA_TASK_ROOT}
  
  # Install the specified packages
  RUN pip install -r requirements.txt
  
  # Set the CMD to your handler (could also be done as a parameter override outside of the Dockerfile)
  CMD [ "lambda_function.lambda_handler" ]

• build & lambda deploy

  #aws ecr login
  aws ecr get-login-password --region {region} | docker login --username AWS --password-stdin {aws_account_id}.dkr.ecr.{region}.amazonaws.com
  # aws ecr repo 생성
  aws ecr create-repository --repository-name {repo-name} --image-scanning-configuration scanOnPush=true --image-tag-mutability MUTABLE
  # build
  docker build --platform linux/amd64 -t {aws_account_id}.dkr.ecr.{region}.amazonaws.com/{repo-name}:{tag} .
  # push
  docker push {aws_account_id}.dkr.ecr.{region}.amazonaws.com/{repo-name}:{tag}
  # lambda create
  aws lambda create-function --function-name {lambda_name} --package-type Image --code ImageUri={aws_account_id}.dkr.ecr.{region}.amazonaws.com/{repo-name}:{tag}
  # lambda update
  aws lambda update-function-code --function-name {lambda_name} --image-uri {aws_account_id}.dkr.ecr.{region}.amazonaws.com/{repo-name}:{tag}