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Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

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Pushing to Multiple Git Repos

If a project has to have multiple git repos (e.g. Bitbucket and Github) then it's better that they remain in sync.

Usually this would involve pushing each branch to each repo in turn, but actually Git allows pushing to multiple repos in one go.

If in doubt about what git is doing when you run these commands, just

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The twelve-factor app Checklist

Also factors in the four principles of modern Release Engineering

• Identifiability Being able to identify all of the source, tools, environment, and other components that make up a particular release.
• Reproducibility The ability to integrate source, third party components, data, and deployment externals of a software system in order to guarantee operational stability.
• Consistency The mission to provide a stable framework for development, deployment, audit, and accountability for software components.
• Agility The ongoing research into what are the repercussions of modern software engineering practices on the productivity in the software cycle, i.e. continuous integration.

Codebase

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// Configure AWS provider
variable "acme_operations" {
  default = "ACCOUNTID"
}

provider "aws" {
  alias = "acme_operations"
  profile = "acme_operations"
  region = "${var.aws_default_region}"
  shared_credentials_file = "./credentials"

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A quick note on how I'm currently handling Blue/Green or A/B deployments with Terraform and AWS EC2 Auto Scaling.

In my particular use case, I want to be able to inspect an AMI deployment manually before disabling the previous deployment.

Hopefully someone finds this useful, and if you have and feedback please leave a comment or email me.

Overview

I build my AMI's using Packer and Ansible.

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A SaltStack AWS Auto Scaling Solution

Overview

The AWS Auto Scaling Goup, configured with a customised Cloud-Init file, sends a notification to an SNS Topic, which in turn passes it onto an SQS queue that the Salt Master is subscribed to. A Reactor watches for the auto scaling events and pre-approves the new minion based on its Auto Scaling group name and instance ID.

Salt Master Configuration

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/* *******************************************************************************************
 * THE UPDATED VERSION IS AVAILABLE AT
 * https://github.com/LeCoupa/awesome-cheatsheets
 * ******************************************************************************************* */


// 0. Synopsis.
// http://nodejs.org/api/synopsis.html

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[
    {
        "city": "New York", 
        "growth_from_2000_to_2013": "4.8%", 
        "latitude": 40.7127837, 
        "longitude": -74.0059413, 
        "population": "8405837", 
        "rank": "1", 
        "state": "New York"
    }, 

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#Create bitbucket branch

##Create local branch

$ git checkout -b sync
Switched to a new branch 'sync'
$ git branch
  master
* sync

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#!/bin/bash


#### SETUP
# 1.) Create a simple point layer
curl -X POST -d '{"layer":"geom","lat":"lat","lon":"lon"}' --header "Content-Type:application/json" http://localhost:7474/db/data/ext/SpatialPlugin/graphdb/addSimplePointLayer

# 2.) Add a spatial index
curl -X POST -d '{"name":"geom","config":{"provider":"spatial","geometry_type":"point","lat":"lat","lon":"lon"}}' --header "Content-Type:application/json" http://localhost:7474/db/data/index/node/