在跑Lambda时，通常需要安装python安装包，这里记录一个自动化方式来完成
构建Docker时，先构建下列文件夹
.
├── container/
│ ├── app/
│ │ ├──app.py
│ ├── Dockerfile
|
├── build_and_push.sh
├── config
├── create_lambda.sh

其中：

• config里面放的是配置

  • s3_path：Lambda运行的代码在s3上的路径
  • docker_name：ECR名字，简称
  • lambda_name：Lambda名字
  • handler：python文件名.程序名，例如app.py中的handler()，则是app.handler
  • s3_bucket：Lambda运行的代码所在的s3 bucket
  • s3_prefix：Lambda运行的代码所在的s3 prefix
  • lambda_role：Lambda运行的Role
  • timeout：超时时间(秒)
  • memorysize：内存大小(MB)
  • ecr：ECR在s3上的全名
  • role：Lambda运行的Role

• container： 中放的是 Lambda 所用的 docker 镜像

  • app：里面放的是要在Lambda里面跑的代码
• build_and_push.sh:是打docker镜像并推导s3上的脚本
• create_lambda.sh：构建Lambda，具体步骤1.把container/app里面的代码打包并上传到s3_path对应的s3目录，2.删除原有的Lambd，3.构建新的Lambda

其中，app.py内容：

import sys
def handler(event, context):
    return '[TEST123] Hello from AWS Lambda using Python' + sys.version + '!' 

Dockerfile内容：

# Define function directory
ARG FUNCTION_DIR="/function"

FROM python:buster as build-image

# Install aws-lambda-cpp build dependencies
RUN apt-get update && \
  apt-get install -y \
  g++ \
  make \
  cmake \
  unzip \
  libcurl4-openssl-dev

# Include global arg in this stage of the build
ARG FUNCTION_DIR
# Create function directory
RUN mkdir -p ${FUNCTION_DIR}

# Copy function code
COPY app/* ${FUNCTION_DIR}

# Install the runtime interface client
RUN pip install \
        --target ${FUNCTION_DIR} \
        awslambdaric

# Multi-stage build: grab a fresh copy of the base image
FROM python:buster

# Include global arg in this stage of the build
ARG FUNCTION_DIR
# Set working directory to function root directory
WORKDIR ${FUNCTION_DIR}

# Copy in the build image dependencies
COPY --from=build-image ${FUNCTION_DIR} ${FUNCTION_DIR}

ENTRYPOINT [ "/usr/local/bin/python", "-m", "awslambdaric" ]
CMD [ "app.handler" ]

make_lambda.sh内容：

zip -r9 function.zip lambda_function.py

aws lambda delete-function --function-name $1

aws lambda create-function --function-name $1 --runtime python3.8 --zip-file fileb://function.zip --handler lambda_function.lambda_handler --role arn:aws-cn:iam::468855463735:role/Lambda_for_SageMaker_Endpoint_Predict --timeout 600 --memory-size 512

create_lambda.sh内容

#!/bin/bash

string=$(cat config | grep s3_path)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 's3_path' ];then
        s3_path=$var
    fi
done

string=$(cat config | grep lambda_name)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 'lambda_name' ];then
        lambda_name=$var
    fi
done

string=$(cat config | grep handler)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 'handler' ];then
        handler=$var
    fi
done

string=$(cat config | grep s3_bucket)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 's3_bucket' ];then
        s3_bucket=$var
    fi
done

string=$(cat config | grep s3_prefix)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 's3_prefix' ];then
        s3_prefix=$var
    fi
done

string=$(cat config | grep ecr)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 'ecr' ];then
        ecr=$var
    fi
done

string=$(cat config | grep role)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 'role' ];then
        role=$var
    fi
done

# zip lambda code and upload
cd container/app/
zip -gr ../../functions.zip .
cd ../../
aws s3 cp functions.zip s3://zbrl-sagemaker-code/temp/

# cd app
# zip -g functions.zip .
# aws s3 cp functions.zip s3_path 

echo s3_path $s3_path 
echo lambda_name $lambda_name
echo handler $handler
echo s3_bucket $s3_bucket
echo s3_prefix $s3_prefix
echo ecr $ecr
aws lambda delete-function --function-name $lambda_name
aws lambda create-function --function-name $lambda_name --handler $handler --role $role --timeout 600 --memory-size 512 --code ImageUri=$ecr,S3Bucket=$s3_bucket,S3Key=$s3_prefix'functions.zip' --runtime python3.8

config内容：

s3_path s3://xxx/yyy/
docker_name lambda/xxxyyy
lambda_name test_lambda
handler app.handler
s3_bucket xxx
s3_prefix yyy/
lambda_role arn:aws-cn:iam::xxx:role/xxx
timeout 600
memorysize 512
ecr xxx.dkr.ecr.cn-northwest-1.amazonaws.com.cn/lambda/xxxyyy
role arn:aws-cn:iam::xxx:role/xxx

build_and_push.sh内容

#!/bin/bash

string=$(cat config | grep docker_name)
array=(${string/// })  
for var in ${array[@]}
do
    if [ $var != 'docker_name' ];then
        docker_name=$var
    fi
done

echo Docker name is : $docker_name

cd container

account=$(aws sts get-caller-identity --query Account --output text)

# Get the region defined in the current configuration (default to us-west-2 if none defined)
region=$(aws configure get region)
region=${region:-us-west-2}

# 如果不是China Region，删掉.cn
fullname="${account}.dkr.ecr.${region}.amazonaws.com.cn/${docker_name}:latest"

# If the repository doesn't exist in ECR, create it.
aws ecr describe-repositories --repository-names "${docker_name}" > /dev/null 2>&1

if [ $? -ne 0 ]
then
    aws ecr create-repository --repository-name "${docker_name}" > /dev/null
fi

# Get the login command from ECR and execute it directly
aws ecr get-login-password --region ${region}|docker login --username AWS --password-stdin ${fullname}

# Build the docker image locally with the image name and then push it to ECR
# with the full name.

docker build  -t ${docker_name} .
docker tag ${docker_name} ${fullname}

docker push ${fullname}