Bill McColl

In big data computing, and more generally in all commercial highly parallel software systems, speed matters more than just about anything else. The reason is straightforward, and has been known for decades. Put very simply, when it comes to massively parallel software of the kind need to handle big data, fast is both better AND cheaper. Faster means lower latency AND lower cost. At first this may seem counterintuitive. A high-end sports car will be much faster than a standard family sedan, but the family sedan may be much cheaper. Cheaper to buy, and cheaper to run. But massively parallel software running on commodity hardware is a quite different type of product from a car. In general, the faster it goes, the cheaper it is to run. Time Is Money As has been noted many times in the history of computing, if you are a factor of 50x slower, then you will need 50x more nod... (more)

The Consumerization of Big Data Analytics

With Dropbox, Jive, Yammer, Chatter and a number of other new services, the modern enterprise is rapidly becoming "consumerized". And it's not just business, the same is happening in major web companies, on Wall Street, in government agencies, and in science labs.  Thirty years of bad "enterprise software" experiences is making this transition happen much more quickly than anyone would have expected. The shift to cloud computing is also accelerating the trend, as is the goal of developing a much more "social" approach to business. The other major change that's going on today thr... (more)

The Intercloud: Turning Computing Inside Out

The intercloud turns computing inside out. With traditional IT, we move the data to where the computing infrastructure is located. With the data volumes in most application areas now growing exponentially, this IT model is now broken. Moving massive volumes of data around means more bandwidth, more storage, and more latency. We need instead to position the computing infrastructure next to where the data is located. With intercloud computing, we can build global apps and services where a single app can operate on data that may be spread across many public clouds and private datace... (more)

The Client-plus-Cloud Revolution

Data is growing exponentially everywhere - in business, web, finance, government, science, and in the world of sensors and smart grids. Speaking earlier this week at OSBC, Tim O'Reilly said  "The future will be all about who has most data, and who is able to extract meaning from it and deliver it in real time".  He noted that the IT industry is now in the process of being reinvented around the idea of realtime analysis of "Big Data" in the cloud, as a must-have adjunct to the much more limited kinds of data processing and analytics that can be performed on desktop PCs or mobile d... (more)

What's Really Industry Changing About Cloud Computing?

Bill McColl's "Cloud N" Blog This is an incredibly important time for the cloud computing area. But let’s try and move the discussion of it in the press along from an obsession with new datacenter buildings located by power stations, with the total server numbers at Microsoft and Google, and with Amazon’s hourly pricing for EC2. Interesting though those aspects of cloud computing appear to be to journalists, they hardly represent what is really industry changing about cloud computing. What are some of the new directions in the massively parallel cloud computing space? I’ll mentio... (more)