Windows Azure, 100% business class

Last week I was with one of Elastacloud’s Big Data customers discussing updating an internal visualisation from around a year ago and looking at how we can turbo charge this. The javascript heavy visualisation shows real time data – a fire hose from their analytics capture partner streams a huge amount of data into a website and a bit of client side work turns that into a list of what’s happening on the site in real time. Pretty nifty.

Sketching out how we could take this from 2012 to 2013 with these industry luminaries was great fun. 2012 was their “year of awakening” to the power of the Cloud and Windows Azure as the best example thereof, giving me the opportunity to take the original idea and add in cloud power. The most amazing part of the cloud is that you don’t need to sketch out on paper. If you’re doing that, you’re missing the point. You sketch it out with compute, running in the cloud as building blocks to your end goal. This isn’t flying economy, it’s flying 100% business class.

We stuck their code in Github in a private repo. We made a few surgical code edits to remove hard coded urls and other nonscalable original design decisions. Using Windows Azure Websites, we replicated their existing (php) infrastructure. We got their system running in minutes with a live link between Github and Windows Azure Websites.

We built a Linux HPC cluster on Windows Azure, empowering their existing R skillset across multiple cores; exposing services that can be consumed to calculate machine learning based algorithms in near realtime, augmenting the live stream firehose with near real time compute – only possible by having hundreds of cores of Linux on Windows Azure at our disposal.

Using Elastacloud’s Azure VM management suite, we can react to the firehose; we can make the Big Compute smarter from the outside world.

A little javascript later and we have augmented 2012′s dumb javascript display to 2013′s cloud powered, machine learning and real time data analysis.

The internal visualisation has a limited use case – it’s used at their bigwig meetings. So we span it up, showed it working, turned it off. Since this is all pay-as-yo-go we could tell them how long and how much that sketching out had cost them, and exactly how much it would cost them ongoing if they wanted the same power for other things.

Those bigwigs can now solve business challenges with real compute assets. “My recommendations cost me £100 a day but make me £1000 a day…” 100% business class.

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