Submitted by MCA Admin 1 on 13 April, 2012 - 23:31
MCA Article Feed.
Ever since we started decentralizing IT resources in the golden-era of client/server (mid-90s), we have been working to reign in the sprawl by consolidation recommendation. As soon as we consolidate, there will be another reason to sprawl (perhaps next time in someone else’s cloud infrastructure). Consolidation has been an effective technique for many years to reduce costs, and it implies several activities and resulting cost reductions:
Submitted by MCA Admin 1 on 13 April, 2012 - 23:31
MCA Article Feed.
It is common to blame vendors and IT service providers with hidden costs. It is true that maintenance fees, transformation services, new training or adjacent system upgrades are required when new equipment is installed.
Source: http://dilbert.com/strips/comic/2009-11-23/
But I also see internal hidden costs within some IT organizations. There are many variations on what might be hidden:
Submitted by MCA Admin 1 on 13 April, 2012 - 23:31
MCA Article Feed.
I have put together a couple blog entries reviewing some cost analysis that I did 2-3 years ago around Hadoop and Azure storage/server architectures–specifically how we worked with customers to reduce the costs of these environments (in part) with enterprise-class storage. It goes without saying—but I will anyway—the focus of these economic models and case studies was on the deployment and costs of the storage infrastructure. Some of these new cloud/big data environments do not use RAID overhead or distribute data across hundreds of nodes and disk clusters to perform the work. As I did this work, we took a myopic view of just the storage hardware aspect of these environments. I guess you would expect that from an HDS employee.
Earlier this week I had an interesting call with Ramon Chen of Rainstor, and compared notes on how they reduce DB costs, and therefore storage with their product offering. After our conversation, it was clear to me that big data cost reductions can happen on at least 2 levels:
Submitted by MCA Admin 1 on 13 April, 2012 - 23:31
MCA Article Feed.
I’m out of the office this week—and I plan on continuing my big data case study series as soon as I return—but quickly wanted to reiterate something Claus posted last week.
Recently, we were able to sit down and cut through the misconceptions to discuss what capacity efficiency really means to us at HDS. And look, someone recorded it!
As Claus mentions, when it comes to capacity efficiency, we are really focusing on data center efficiencies, improving performance and consolidation—which gives us a pretty unique positioning in the marketplace.
So if you have a few minutes, check it out, and let us know what you think.
And for the record, I don’t think there’s anything wrong with the haircuts in the video…
Submitted by MCA Admin 1 on 13 April, 2012 - 23:31
MCA Article Feed.
I have been developing a small mini-series on the economics of big data, with a focus on the storage approach used in Hadoop and Azure architectures. The intro blog, case study #1, and a review of bare-metal analysis have been posted to this blog over the past few weeks. I will wrap up this series with another case study, this time with a Hadoop environment.
Like so many organizations that embark on a new IT infrastructure/architecture, the start-up investments are such that planners and procurement are price sensitive. Getting a Hadoop environment genned-up can be very easy, and relatively low in cost. This is true for our case study #2 client, who is a large online retailer.
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