kangks

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
import json
import requests
from pyspark import sql
from uuid import UUID

kangks

AWSTemplateFormatVersion: '2010-09-09'
Metadata:
  Comment: "Stack for S3 event -> Lambda transform from csv to json -> kinesis stream -> downstream Lambda for each row processing.
  These are the purpose of the demo:
    - Retry of downstream Lambda when failed. The record in Kinesis Stream will not be removed until success Runtime
    - With large CSV, the Lambda will parallel according to number of shards of Kinesis Stream"
Resources:
  IAMRole:
    Type: "AWS::IAM::Role"
    Properties:

kangks

{
  "AWSTemplateFormatVersion": "2010-09-09",
  "Description": "Create AMR Cluster",
  "Parameters": {
    "ProductParam": {
      "Description": "The EMR Product tag",
      "Type": "String",
      "Default": "aProductParam",
      "MinLength": "3",
      "MaxLength": "50",

kangks

{
  "AWSTemplateFormatVersion": "2010-09-09",
  "Description": "Create Linux EC2 with postgresql96",
  "Metadata": {
    "Comment": "Postgres 9.6 on a r3.8xlarge + 20G EBS in a privateSubnet, and pgbench in publicSubnet"
  },
  "Parameters": {
    "Ec2KeyNameParam": {
      "Description": "Name of an existing EC2 KeyPair to enable SSH access to the instance",
      "Type": "AWS::EC2::KeyPair::KeyName",

kangks

import boto3

required_keys = [ "key01", "key02", "key03", "key04" ]
ses_source = 'source@maildomain.com'
ses_destination = ['somebody@domain.com']

def lambda_handler(event, context):

    if 'detail' in event and 'instance-id' in event['detail']:
        ec2_instance_id = event['detail']['instance-id']