Thought Leaders in Cloud Computing: Steve Garrou, VP of Global Solutions Management, Savvis (Part 3)

Sramana Mitra: Let me pick up on a few things you said and drill down on those. You were talking about “back to the future” as in we went to this client–server model, a more distributed model, and now we’re going back to a centralized, hosted solution that is accessed by [thin] clients, and in some cases, rich clients, all over the world.

Steve Garrou: Yes, that’s definitely part of it, the technology of “back to the future.” And we see the pendulum swinging back and forth from client server to thin client and then back to distributed [and] decentralized. We actually see that. >>>

Thought Leaders in Cloud Computing: Steve Garrou, VP of Global Solutions Management, Savvis (Part 2)

Sramana Mitra: What are the major trends you see in cloud computing today that are affecting your world?

Steve Garrou: We’re finding that cloud is driving a lot of strategic conversations, almost as much as the technical ones. What we’re seeing with our clients – I mentioned I was in Asia – this is in Singapore, with a client that is looking at going completely toward cloud or as-a-service delivered capabilities for their infrastructure. There were a number of points in what they told us. First is this notion of consumer IT so that end users, much like those of us on the phone, are interested in taking advantage of the types of data and applications we get on our mobile phones and tablets and being able to use those devices, that data, and those types of applications inside the enterprises, not just in their personal lives. We see that driving a lot of these types of decisions. >>>

Thought Leaders in Cloud Computing: Steve Garrou, VP of Global Solutions Management, Savvis (Part 1)

Since making its initial public offering in February 2000, Savvis has experienced significant growth, not only organically but also through acquisition. When the company decided to expand its operations in 2005 from network services to global IT services, a name change went along with it, and Savvis Communications became Savvis, Inc. In 2007 and 2008, the company opened offices in Singapore and London, respectively. In 2011, Savvis, Inc. and CenturyLink merged to create one of the leading global managed hosting and colocation providers.

SramanaMitra: Hi, Steve. Let’s set a bit of context both about your personal background and about Savvis. >>>

Thought Leaders in Cloud Computing: Ari Zilka, CTO of Terracotta (Part 7)

SM: There are many classifications of big data and real time. At this point, that’s one of the reasons why there’s so much activity in the space right now.

AZ: Yes. Big data can be sold to enterprises because no matter who you are, you don’t have to be a Facebook anymore to have an explosion of data on your hands. Big data can be sold to the end user. It’s purely a function of context. There are companies like Backblaze and Blaze Logic and Dropbox and Box.net selling data management in the cloud. There is big data for you and me. There is big data for Main Street enterprise. There’s big data for Wall Street. There is big data in different flavors and slices all over the place, helping us manage the fact that all our data has moved online. At some point, the IRS said, “Please don’t send me any paper tax returns. I don’t want to file anything anymore. I’m happy to buy disks. I’m not very happy to buy file cabinets.” If the IRS is online and they’re handling big data, and you’re not thinking about it for your business and your customers, then you’re behind the curve … absolutely. >>>

Thought Leaders in Cloud Computing: Ari Zilka, CTO of Terracotta (Part 6)

Sramana Mitra: OK, as a follow-on question – this is a good, visceral example to illustrate what you’re talking about. Why has Twitter not been able to monetize along those same lines? It’s similar to Facebook, but Twitter has not succeeded in leveraging the big data/real time element of their infrastructure, why not?

Ari Zilka: Twitter is both big data and it’s real time. Twitter could comb through their Tweets, their end user Tweets, and look for patterns in what people are Tweeting about. That’s the hashtags, in fact, where users self-tag as part of a pattern and a trend. Twitter then looks at those hashtags and the symbols’ trends. It also does regular pattern matching on our Tweets. It also has a real-time aspect. The entire interface to Twitter is about a real-time push of data between you and me and all our friends in our networks and so on. So, your question is excellent. Why aren’t they making money? >>>

Thought Leaders in Cloud Computing: Ari Zilka, CTO of Terracotta (Part 5)

Sramana Mitra: I have to say, though, that what you’re describing, even at a big data level, not yet available. Forget big data and real time. Correct?

Ari Zilka: That’s where Terracotta comes in. We’re a data management company, and the product’s name is Big Memory.

SM: I know, but what I am saying is you can add the real-time component to it, but the truth is the big data analytics portion of it is not available yet. >>>

Thought Leaders in Cloud Computing: Ari Zilka, CTO of Terracotta (Part 2)

Sramana Mitra: So, the way end customers access your product is through other application vendors that are using your product to develop their applications?

Ari Zilka: It’s a 50-50 split. Half the world doesn’t even need to know we’re there. They use other applications that use us. We help those vendors sell our product to the customers to get more scale, more throughput. And then half the customers have end developers in-house who go to our site directly, download our products, and integrate them by hand into their own business logic. So, it’s not just for packaged apps. It’s also for custom apps. >>>

Thought Leaders in Cloud Computing: Ari Zilka, CTO of Terracotta (Part 1)

Founded in 2003 by Ari Zilka, Terracotta, a wholly owned subsidiary of Software AG, develops breakthrough software that delivers snap-in performance, scale, and availability for enterprise applications. Terracotta’s technology can store up to a terabyte of data in-memory, which can boost application and system performance and scalability significantly. At the time of its acquisition in June 2011, the company had 55 employees located in development centers in San Francisco and New Delhi. The company’s customer base is filled with names like JP Morgan, Adobe, BBC, and Hitachi, among others.  >>>