The Mainframe Bridge to the Cloud

How can mainframes can help enterprises reach cloud-computing benefits faster? Let’s look at what defines cloud computing, with an emphasis on private clouds or those computing models that enterprises can control on-premises, but that also favor and provide cloud-like efficiency with lower-end costs and a heightened ability to deliver services that support agile business processes.

We’ll examine how new developments in mainframe automation and supporting the use of mainframes allow for cloud-computing advantages and the ability to solve some of the more contemporary computing challenges.

To help us understand how mainframe is the cloud, we’re joined by Chris O’Malley, executive vice president and general manager for CA’s mainframe business unit. Welcome to the show, Chris.

Chris O’Malley: Dana, thank you very much. I’m glad to be here.

Listen to the podcast (35:00 minutes).

Gardner: Chris, we’ve heard a tremendous amount about cloud computing and there’s a buzz around this whole topic. From your perspective, what makes cloud so appealing and feasible right now?

O’Malley: Cloud as a concept is, in its most basic sense, virtualizing resources within the data center to gain that scale of efficiency and optimization you just discussed. It’s a big topic of discussion right now, especially given the recession we’re sitting in.

It’s very visible physically that there are many, many servers that support the ongoing operations of the business. CFOs and CEOs are starting to ask simple but insightful questions about why we need all these servers and to what degree are these servers being utilized.

When they get answers back and it’s something like 15, 10 or 5 percent utilization, it begs for a solution to the problem to start bringing a scale of virtualization to optimize the overall data center to what has been done on the mainframe for years and years.

We’re now seeing the availability of the technology — VMware is an example — to start to create almost mainframe-like environments on the distributed side. So, it’s both the need from a business standpoint of trying to respond to reduced cost of computing and increased efficiency at a time when the technologies are becoming increasingly available to customers to manage distributed environments or open systems in a way similar to the mainframe.

Gardner: I suppose there’s also an issue around integration. When people talk about cloud computing, we hear them refer to it as an application-development or Platform as a Service (PaaS) affair. We also hear Software as a Service (SaaS) or just great delivery of the applications. Then, there’s this notion of infrastructure fabric or Infrastructure as a Service (IaaS).

But to relate and manage all of those things is something we haven’t yet seen in this whole cloud market. I imagine that at a private level, if you were to use mainframe and associated technologies, you might start to see some of those integration points among these different levels or aspects of cloud computing.

O’Malley: You’re right. It’s a maturity curve that we’re going through, and it’s very likely that larger customers are using their mainframe in a highly virtualized way. They’ve been doing it for 30 years. It was the genesis of the platform. It’s a fixed asset that was very expensive way back, or at least relatively expensive, that they try to get as much out of it as they possibly can. So, from its beginning, it was virtualized.

You see the same big customers, though, having application needs outside of what they’ve done themselves. What customer relationship management (CRM) and Salesforce.com have done creates a duality of the mainframe acting as a cloud and using SaaS to support how they work their markets. It’s very important that those things start to become integrated. CRM obviously fits into things like order entry, and tying those efforts together.

As you go through this maturity cycle, there is always a level of effort to integrate these things. The viability of things like Salesforce.com, CRM, and the need to coordinate that data with what for most customers is 80 percent of their mission-critical information residing on the mainframe is making people figure out how to fix those problems. It’s making this cloud slowly, but pragmatically, come true and become a reality in helping to better support their businesses.

Gardner: So, that would lead, at some point, to a cloud of clouds and hybrid models. We’ve been worried about integration vertically and now horizontally. I suppose we’ll have to start worrying about it across organizational boundaries as well.

O’Malley: Absolutely. There are other barriers that exist as well. The distributed environment and the open system environment, in terms of its genesis, was the reverse of what I described in the mainframe. The mainframe, at some point, I think in the early ’90s, was considered to be too slow to evolve to meet the needs of business. You heard things like mounting backlog and that innovation wasn’t coming to play.

In that frustration, departments wanted their server with their application to serve their needs. It created a significant base of islands, if you will, within the enterprise that led to these scenarios where people are running servers at 15, 10 or 5 percent utilization. That genesis has been the basic fiber of the way people think in most of these organizations.

It’s not just the technical barriers and the complexity of it. It’s a cultural shift of an acceptance by players across the business. They all start to use a shared commodity in fulfilling their needs, and the recession helps that. Good CEOs and good CFOs never let a recession go to waste. They explain to their executive management, “We need a greater level of efficiency. We need to transform our thinking, so that we can start to take advantage of these technologies, decrease our overall cost, and increase our ability to serve our market.”

They are not just technical issues. There is also people’s disposition on the way IT should be run. That has to change as well.

Gardner: I suppose we’ve gone along with the pendulum swing, from centralized, to decentralized, and now we’re coming back. I’ve spoken to a number of people that say the shortcomings of distributed computing are, in fact, the set of requirements for cloud computing. Do you agree with that?

O’Malley: I absolutely do. This 15 or 10 percent utilization is what we consistently see, customer after customer after customer. Recently, I was with an international customer. They took me on a data center tour, and one of the first things I see is an air conditioning unit the size of a school bus. I see walls that are three-and-a-half feet thick, poured concrete. I see cabling that looks like it weighs tons and football fields of floor space. In the midst of the tour, somebody tells me, “Here is a blade server that cost us next to nothing.”

The difficulty in bringing and using these things in an efficient fashion, the cost of all those moving parts, and everything that has to be managed as a single thing, rather than in a virtualized form, has caused a scale of waste that you cannot hide.

Time and time, I hear there is not a CEO or a CFO interested in adding yet another square foot of data-center floor space or adding people to manage the environment at a scale equal to the increasing capacity. They should be getting economies of scale and are just not seeing it.

You’re seeing the pendulum come back. This is just getting too expensive, too complex, and too hard to keep up with business demands, which sounds a lot like what people’s objections were about the mainframe 20 years ago. We’re now seeing that maybe a centralized model is a better way to serve our needs.

Gardner: A lot of what attracts people to the cloud model — because it is still rather amorphous, and not well-defined — is this notion of elasticity. That’s both, as you say, to help on utilization when it’s low, but also to allow for the spikes to be managed externally or to take workloads and apply them across multiple machines in the case of a private cloud.

O’Malley: Exactly.

Dana Gardner is president and principal analyst at Interarbor Solutions, which tracks trends, delivers forecasts and interprets the competitive landscape of enterprise applications and software infrastructure markets for clients. He also produces BriefingsDirect sponsored podcasts. Follow Dana Gardner on Twitter. Disclosure: CA sponsored this podcast.

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