BYOD: Bring Your Own Disaster

In keeping with the tradition of the last three to five years, 2012 is being touted by analysts and vendors alike as "the year for VDI." This year there is a slightly new twist to the hype and marketing, and that’s Bring Your Own Device (BYOD). It’s a simple concept: Employees own devices that they like to use and are most productive on; IT should support the apps and services used to run the business on the employees’ devices. To see the full post visit:

GD Star Rating

Hybrid Cloud’s Burst Bubble

One of the more hyped use-case examples for hybrid cloud is cloud bursting. And why not? It’s truly the have-your-cake-and-eat-it-too scenario. During normal business operations, your systems run in-house on private cloud infrastructure, and during unforeseen or unpredictable peaks, your services burst to excess capacity at your public cloud provider(s) of choice. It’s IT utopia, right? It’s the comfort of maintaining your own systems with the insurance of endless available capacity for the unknown. To see the full post visit:

GD Star Rating

Horton Hears Hadoop

I’m feeling Seuss-ish so here goes (Line 1 and 2 by Ken Oestreich @fountnhead.)


Of this poem you should first realize, of course,

Is based on Big Data, and code open-source.

On disk that was spinning… sat data quite large…

So much that in fact it would fill up a barge.


This data had value.  To realize it hard.

The data named Horton.  His contents were barred.

You see to run queries, we needed some help,

Then one day from Yahoo came a very faint yelp.

I’ve got it said Yahoo, we call it Hadoop!

Just give us a minute, we’ll give you the scoop.

With this new fangled tool, value we’ll recoup.


So Horton sat patient, while Yahoo did tell.

Of a man named Doug Cutting, here we will dwell.

Horton, you are so large your values obtuse.

But we can fix that, with a tool MapReduce.

This tool comes from Google, it’s really quite great.

With it and Apache, your value awaits.


We’ll take your large size, distribute it broadly.

Place it on servers, with scale of an army.

Each will have data that sits there quite local.

Data divided and sent as a parcel.


You see with this method my very large friend.

We’ll run great queries watch your value transcend.

Task Trackers / Data Nodes will do all the work.

You’ll be the big hero, no longer the jerk.


With Name Node in charge of tracking the data.

Job Tracker oversees slaves alpha to zeta.

The workload is spread, we parallel process.

To make some sense of this big data nonsense.


With the power of scale, the smallest of all,

Can still have a seat at the processing ball.

They’ll all work in tandem to help sort you out.

And this my friend, is what Hadoop is about.

GD Star Rating