IBM, the Cloud, Big Data
The launch of the social collaboration services that will be delivered on IBM’s Federal Community Cloud should give it an added grip in the public sector where the benefits of social media seem to be finally sinking in.
With the Big Data announcement, which was made only a matter of days after Microsoft announced its vision of Big Data management using the Azure cloud, Big Blue appears to have slashed the amount of time it takes to scan all the files on an enterprise system.
While the announcements are independent of each other, it demonstrates the fact that, while IBM is looking to extend the reach of its cloud computing offerings, it is also developing technologies that will make the cloud more efficient.
IBM’s Social Collaboration
So first let’s take a look at the new social collaboration services IBM is offering. The cloud services include a whole array of what are, at this stage, old social media tools.
These include wikis, microblogs, communities, staff profiles, instant messaging, web conferencing and email, as well as support for mobile devices including Android phones and tablets, Apple iPhone 4 and iPad, BlackBerry and Nokia Symbian platform.
Not exactly groundbreaking, but given the current US administration’s obsession with IT efficiencies, quite a smart move, especially given thatthis will be offered on IBM’s Federal Information Security Management Act (FISMA)-compliant cloud, an offering, in principle, that comes with top-drawer security.
Here’s what Todd S. Ramsey, General Manager, IBM U.S. Federal had to say about it:
The rise in Big Data and the demand for transparency and collaboration will continue to put pressure on agencies to embrace new computing environments such as cloud to improve IT capabilities…”
Extending IBM’s Big Data
So it’s probably fortunate, then, that IBM is also working on Big Data, and the timing of this announcement really has to make you smile.
You may recall last week that Microsoft announced a set of tools, the result of a research project into Big Data computing called Project Daytona.
With Project Daytona, Microsoft says it has developed a runtime version of Google's open-license MapReduce model for Windows Azure that will support a range of analytics and machine-learning algorithms and can be scaled out to hundreds of server cores for analysis of distributed data.
Not to be upstaged, only a couple of days after, Big Blue announced thatit had successfully scanned 10 billion files on one system in 43 minutes, beating the previous record of one billion files in three hours by a factor of 37.
With it, enterprises will be able to unify data environments on one platform instead of having them distributed across several systems that have to be managed separately and reduces the amount of physical hardware needed.
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The announcement, which IBM is calling a "breakthrough," streamlines its General Parallel File System (GPFS), first introduced more than ten years ago.
The result is that, using GPFS running on a cluster of 10 eight-core systems and solid state storage, it took only43 minutes to perform the scan.
The GPFS management rules engine provides the comprehensive capabilities to service data management tasks.
Without getting into the technical details, this means that one platform will be able to reduce and simplify data management tasks such as data placement, aging, backup and migration of individual files.
If you were a really bad-minded person, you might think IBM was doing this -- or at least announcing this -- just to annoy Microsoft.
But think about IBM’s portfolio of products, particularly across business intelligence, and it makes sense for it to develop Big Data storage products.
Last year alone, the amount of digital data increased 47% -- IBM's figures -- putting businesses under pressure to turn data into actionable insights, but grapple with how to manage and store it all.
IBM offers a range of packages in this area, and only recently announced Big Data analytics based on its Netezza acquisition.
It’s not clear when IBM will apply this new storage ability, but clearly, if it is to monetize on its analytics stable fully, it will be pushing to do this sooner rather than later.
