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Cloud Computing for Everyone

The DIY app revolution

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In computing, big revolutions happen whenever a new technology comes along that enables everyone to do something that could previously only be done by a small number of technology experts, or only by those with tons of money and technical talent. Personal computing (Microsoft, Apple), Publishing (Adobe), Search (Google), Video (YouTube), News/Journalism (blogs) are all examples of this kind of disruptive revolutionary change. What's the next big game changer? In a word - Apps! We are about to move to an era in which everyone will be able to build their own apps - business apps, web apps, financial apps,...



Until recently, when we thought about business applications, we thought about the kinds of big software systems sold by SAP, IBM, Oracle and the like. In practice, much of what keeps businesses going is the vast numbers of "small apps" developed by hundreds of millions of business professionals around the world, using tools such as Microsoft Excel. These are "DIY Apps" and they're becoming more and more common, as business professionals bypass the delays and complexity they, rightly or wrongly, have come to associate with IT departments and "enterprise software" solutions.

In the web world it's the same, the iPhone AppStore has changed how we think about the "software industry". Is that student in his dorm room, developing his iPhone app for sale, really part of the software industry? It's like asking whether someone who uploads a funny video to YouTube is part of the entertainment industry. DIY videos, DIY iPhone apps, DIY Excel business apps - the trend is clear, more and more people will be writing apps in the future. Which means that it has to get much, much easier!

Why can't an individual portfolio trader in the rural midwest compete with Goldman Sachs and other Wall Street firms? Why can't an individual in an enterprise quickly develop a realtime app to track some live data that's key to what they're working on. Why are there 100 small companies created solely to analyze the Twitter stream in different ways. Why can't I do that myself? Same for blogs, news, sensors, financial market data, clickstreams,...

In the past, the answer was simple. Those with the need for an app didn't have the scalable server, network and storage infrastructure to do it themselves. They also didn't have the teams of programmers required. Today, the first "reason" is rapidly disappearing, as cloud vendors provide all that commodity iron at hourly rates. To eliminate the second reason, we need new tools that enable non-programmers to develop powerful apps themselves. Excel is a great starting point, as it's already used by more than one hundred million business professionals to generate DIY apps of all kinds. So at least we have a proof of concept - use Excel! But Excel has no elastic scalability, no realtime capability, and no parallel processing of the kind required to handle the "Big Data" challenges now spreading throughout business, web, finance and government.

Next month Cloudscale will be commercially launching the Cloudcel platform, a realtime, massively parallel cloud platform for Big Data Apps. Usable in minutes by anyone who can use Excel, Cloudcel enables non-programmers to simply and quickly develop powerful new DIY Apps on massive data sets and live data streams.

Cloud computing really is a game changer. It provides an infrastructure on which it is now possible for hundreds of millions of non-programmers to become serious app developers. That sounds like a bit of a revolution!

More Stories By Bill McColl

Bill McColl left Oxford University to found Cloudscale. At Oxford he was Professor of Computer Science, Head of the Parallel Computing Research Center, and Chairman of the Computer Science Faculty. Along with Les Valiant of Harvard, he developed the BSP approach to parallel programming. He has led research, product, and business teams, in a number of areas: massively parallel algorithms and architectures, parallel programming languages and tools, datacenter virtualization, realtime stream processing, big data analytics, and cloud computing. He lives in Palo Alto, CA.

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