Such services won't necessarily live in the public cloud, he said. Customers may work with a managed service provider offering private cloud services, build a private cloud behind an internal firewall or go with a private cloud managed by CA. "Our view is that how SaaS is delivered is less important than the underlying attributes of the SaaS model," Gregoire told customers. "For us, SaaS is about higher customer intimacy, great engineering, multiple releases and a quality of code higher than we have ever seen before. It's about sharing detailed roadmaps and helping you move from customizing software to configuring software."
No tech executive speech would be complete without an obligatory reference to the growing petabytes -- nay, zettabytes -- of data businesses and consumers are generating each year. "We can talk all we want about big data," Gregoire said, "but masses of data aren't very useful unless we have the means to mine and analyze all that information for insight and business value." For starters, CA's existing stable of products will help companies manage and secure that big data. More ambitiously, Gregoire said the company sees an opportunity to help customers analyze the reams of data they collect from their CA network, system and application management and security systems in order to help them optimize their IT environments -- sort of what recent IPO darling Splunk helps customers do with their machine log data, but on a wider internal scale.
"One of the advantages we have over a lot of new companies getting into the management analytics game is that we have the data," Gregoire said, noting that CA software analyzes 600 million mainframe records, closes out more than 380 million trading transactions, processes more than 42 million authentications and monitors more than 100,000 devices on global networks every day. He added: "With the right analytics, this data could help [customers] develop new products, introduce new services and identify new market opportunities." For example, he said CA is helping a customer use big data to improve online fraud analytics.
But it's unclear how CA plans to approach this opportunity. Will it build analytics capabilities into its management and security software? Will it partner with analytics vendors to offer consulting or other services? Gregoire would say only that CA intends to "leverage this technology in future products and solutions."
The strategy sounds familiar. In the late 1990s, CA touted how its patented "Neugent" (queue up "Cat Scratch Fever") artificial intelligence technology would help customers analyze network and system information to forecast outages and other problems and plot their infrastructure management strategies. But that predictive analytics effort amounted to little more than vaporware. CA still has a lot to prove here.
Gregoire isn't oblivious to customer skepticism, ending his keynote: "Technology is always about the future, about the next big thing. Sometimes it pans out, sometimes it doesn't. And people in IT tend to be realists. You've heard the hype too many times."
He added: "We don't underestimate the challenges, for you or for ourselves, but we think they pale next to the opportunities. It all comes down to a question I asked in the beginning: Are you going to drive these changes, or are you going to be driven by them?"