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The Cloudcast: Technology Warfare and the Evolution of Cloud Economics

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The Cloudcast: Technology Warfare and the Evolution of Cloud Economics

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The Cloudcast (.net) #51 - Technology Warfare and the Evolution of Cloud Economics.mp3 (49:55)

Date: August 22, 2012

By: Aaron Delp and Brian Gracely

Description: Aaron and Brian talk with Simon Wardley (@swardley) - Researcher, Organization Warfare and Evolution at LEF, about the evolving economics of Cloud Computing, open-source strategy and the current wartime environments for technology companies.

Simon at OSCON 2009 - “Cloud Computing - Why IT Matters

Simon at OSCON 2010 - “Situation Normal, Everything Must Change

Topic 1 - You’ve mentioned a number of times that we’re currently in a state of “war” within IT technology, which is different that a “peacetime” environment. Can you elaborate on what that means, and more importantly, are there any rules during war time?

Topic 2 - Recently you stated (or commented on another statement) that in order to compete as a Cloud provider these days, that a company would need to invest ~ $500M per year. What does that mean for the existing and emerging “service providers”, and does that eventually mean we’ll evolve to some small number of Cloud providers (eg. 10-12) around the world?

Topic 3 - You mention in a recent blog that you’d recommend VMware create a commodity, open-source Cloud offering, and suggested they use Cloudstack as the IaaS portion (along with Cloud Foundry). Why not OpenStack? Please talk about the AWS API in either of these context?

Topic 4 - In your talks, you mention that innovation (as a competitive differentiation) is just one phase of the technology lifecycle and that it’s nearly impossible to sustain, due to things like open-source and the drive for quarterly profitability. You’ve sighted that as one of the reasons you predict that Apple will ultimately crumble. Is this something that can actually be transitioned by an existing company?

Topic 5 - You mentioned that you feel very confident in your models and predictions, but you typically don’t put timeframes on them. What are the key “events” you look for that your models are beginning to play out, or need to be adjusted? 


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