Auto Tag EC2 Spot Instances and Volumes with Boto

Tags are a great way to organize Amazon Web Services (AWS) resources. For example, you can use tags to itemize your AWS bill into different projects. Unfortunately, with spot requests, there is no automatic way to tag the EC2 spot instances and EBS volumes once the spot request has been fulfilled. Here is one way to do that using boto, the Python SDK for AWS.

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How To: CRUD with Validation in Ember.js Using ember-easyForm, ember-validations, and Boostrap

One of the basic building blocks of any web application is CRUD, or Create, Read, Update and Delete. It allows users and administrators to manage the data in the application. Full-stack server-side MVC frameworks like Django or Ruby on Rails provide code generators that give you all the code needed for a basic CRUD interface. But what if you were using Ember.js to build your application? Ember.js does not provide any code generators, and there is no established idiom or best practices for CRUD in Ember.js. In this series I will show how to build a basic CRUD interface in Ember.js, complete with user input validation.

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Is Mining Litecoins on AWS EC2 Profitable? PART 2: GPU Mining


In part 1, we looked at mining Litecoins on CPUs rented from Amazon EC2. Now, let us see if we can get better performance by mining Litecoins using GPUs.

Using CPUs, we were able to achieve an average hash rate of 144 KH/s using Amazon EC2’s c3.8xlarge instances, that come with 32 CPUs. Recently, Amazon made available their new generation of GPU instances, called g2.2xlarge, that provide access to NVIDIA GRID GPUs (“Kepler” GK104) each with 1,536 CUDA cores and 4GB of video memory. GPUs are supposed to provide better performance than CPUs when mining Litecoins. Is this true of the virtual computing instances provided by Amazon EC2? Let us find out.

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Is Mining Litecoins on AWS EC2 Profitable? Part 1: CPU Mining

With the value of Bitcoins soaring to record highs, hitting USD 1,242 on 29 Nov 2013, many might be tempted to join in the gold rush of Bitcoin mining. But the competition is fierce, and the difficulty level has risen to a level that makes Bitcoin mining unprofitable for most except those with highly specialized equipment.

Enter Litecoin, the silver to Bitcoin’s gold, which similarly rose to a record USD 48.48 on 28 Nov. Unlike Bitcoin, which uses the SHA256 algorithm that requires specialized hardware called ASICs for maximum performance today, Litecoin “uses a memory-hard, scrypt-based mining proof-of-work algorithm to target the regular computers and GPUs most people already have.” In other words, it is designed for people with commodity high-performance CPUs and GPUs to participate in. What if you do not have a high-performance CPU or graphics card to mine Litecoins with? How about renting them, say from Amazon Web Services (AWS)? In this two-part series, I shall examine whether it is profitable to mine Litecoins with CPUs and GPUs rented from AWS.

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Free Book: Introduction to Data Science, Version 2.0 By Jeffrey Stanton & Robert De Graaf

Introduction to Data Science, Version 2.0 is a free e-book written by Jeffrey Stanton, Professor and Senior Associate Dean in the School of Information Studies at Syracuse University, and Robert de Graaf. It was developed for the Certificate of Data Science program at the School, and serves as an introduction to the key concepts of data science for non-technical readers. The book uses a hands-on learning approach, walking readers through data science concepts and tasks using the R language. It is suitable for anyone who wants to have a slightly technical appreciation of what data science is about, and an understanding of what data scientists do.

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Learning the Norman Layout, Week 3

This is the end of my third week learning the Norman keyboard layout. Learning a new layout is quite a big endeavour, as it changes the way I do almost anything, both at work and at home. How well I learn it determines how efficiently I can go about my daily tasks, and how frustrated I get when I make mistakes that slow me down and get in the way. So how is my typing now, after three weeks of practise?

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Learning the Norman Layout, Week 1

It has been a week since I started learning the Norman keyboard layout. I went “cold turkey”, diving right into the new layout after just a couple of days. During the first few days, typing required a conscious effort to watch where my fingers were going, and where each key was supposed to be. I made lots of mistakes, which slowed me down somewhat. By the end of the first week, I found myself getting gradually more comfortable with the new layout.

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