mgla

Random useful Athena queries

CloudTrail

Find out who modified a IAM user policy

SELECT eventname,
         useridentity.arn,
         sourceIPAddress,

eventtime,

victoriadrake

package main

import (
	"math/rand"
	"net/url"
	"os"
	"time"

	"github.com/ChimeraCoder/anaconda"
	"github.com/Sirupsen/logrus"

omerxx

Resources:
  Service: 
    Type: AWS::ECS::Service
    DependsOn: ListenerRule
    Properties: 
      Cluster: !Ref Cluster
      ServiceName: !Ref ServiceName
      LaunchType: !Ref LaunchType
      DesiredCount: !Ref DesiredCount
      DeploymentConfiguration: 

chrisdpa-tvx

All Your Data Does Not Belong In a Database

Businesses are machines producing mountains of data about sales, usage, customer, costs, etc... Traditionally data processing is highly centralised with teams of staff and computer running hot a whirling ready to process. We can do better than moving the mountain of data into the corporate data machine - so long as that machinary is light enough to be moved to the data.

Don't move the mountain - Bring the processing to the data

We've had this problem; a huge directory of files in CSV format, conataining vital information for our business. But it's in CSV, requires analysis, and don't you don't feel like learning sed/grep/awk today - besides it's 2017 and no-one thinks those tools are easy to use.

zenmaster24

import boto3
import json
import datetime
import time
ec2 = boto3.resource('ec2', region_name='ap-southeast-2')

filters = [{
	'Name': 'tag:snapshot',
	'Values': [ 'yes' ]
}]

sjparkinson

---
AWSTemplateFormatVersion: 2010-09-09

Description: >
  A basic CloudFormation template for an RDS Aurora cluster.

Parameters:
  DatabaseUsername:
    AllowedPattern: "[a-zA-Z0-9]+"
    ConstraintDescription: must be between 1 to 16 alphanumeric characters.

badboy

OnlyInAmerica

# Find the IAM username belonging to the TARGET_ACCESS_KEY
# Useful for finding IAM user corresponding to a compromised AWS credential

# Requirements:
#
# Environmental variables: 
# 		AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY
# python: 
#		boto

Eugeny

#!/usr/bin/python
# -*- coding: utf-8 -*-

import subprocess


__all__ = ["transform"]
__version__ = '0.3'
__author__ = 'Christoph Burgmer <cburgmer@ira.uka.de>'
__url__ = 'http://github.com/cburgmer/upsidedown'

patrickwelker

<time datetime="{{ post.date | %Y-%m-%d %H:%M+01:00 }}">
         {{ post.date | date: "%d. %B %Y" | replace:"January","Januar" | replace:"Februar","February" | replace:"March","März" | replace:"May","Mai" | replace:"June","Juni" | replace:"July","Juli" | replace:"December","Dezember" }}
</time>