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The New Mainframe Normal

The maturity model helps improve processes for performance and cost as systems converge

3/5/2014 12:04:27 AM | With the introduction of the first zEnterprise machine, the z196, it should have become apparent that this was no longer your father’s mainframe. The mainframe became the centerpiece of a hybrid computing environment that embraced z/OS, Linux, Power and Windows running on x86 blades.

Not only was the mainframe changing but the entire computing world was changing. The mainframe was serving up data and processing to mobile devices. Banks, the most stalwart of mainframe users, were scrambling to run increasing volumes of online transactions generated from mobile customers using smartphones. The clean, tightly controlled world of the mainframe was spiraling into a multi-platform, multi-OS-, multi-API- and multi-services-driven world where complex transactions could initiate and run from and across any device, anywhere, anytime.

The rise of big data and analytics further complicated the mainframe data center. An appeal of the mainframe has always been the proximity of core transaction data. Now the range of the data to be analyzed went beyond DB2 transactions and IMS data to encompass unstructured social and mobile data, machine-to-machine data (the Internet of Things) and more. And results often had to be produced in near real time.

Suddenly the mainframe development team found itself architecting compound workloads across the mainframe and multiple distributed systems running both Windows and Linux and, sometimes, AIX. And the volume of real-time transactions the operations people were handling was surging: Millions of transactions seemed small when billions of transactions were looming.

Welcome to the new mainframe normal. It assumes a new style of computing that encompasses mainframe and distributed systems and mobile and social workloads running alongside traditional mainframe workloads. It expects high volume analytic processing running concurrently with high volume transaction processing. And if your mainframe data center is to survive, it will need to accommodate this new normal.

A New Mainframe Maturity Model

Maturity models are a traditional tool for organizing and understanding the workings of complex systems. The mainframe maturity model that most mainframe shops are organized around is probably several decades old, predating the rise of distributed systems; ubiquitous networking; the Internet; and certainly the cloud, mobile and social computing.

Maturity models help organizations improve processes amid change. A newly developed mainframe maturity model, maybe better described as an enterprise IT maturity model, can help IT organizations improve processes for managing application performance and mainframe costs as distributed and mainframe systems converge.

The new model, on the surface, may not look all that different from the old model. Both portray a hierarchical structure representing increasing levels of sophistication at each layer. The differences show up mainly in the higher levels. Perhaps the most disconcerting change for traditional mainframe shops will be the embrace of distributed, open systems (systems of engagement) alongside the traditional mainframe environment (systems of record). And with that comes the need to bridge a gap that has long existed between mainframe and distributed teams. Closing that gap is no longer an option–it has become a business imperative.

Another shift the new maturity model brings out is the changing role of the mainframe. It has evolved from a tightly managed processing center for the most efficient, lowest cost operations to, instead, an integral part of the business application delivery chain as well as a potential revenue generator. The revenue-generating potential of the mainframe becomes most apparent through its analytics processing capabilities that surface valuable business insights and enable competitive advantage.

Inside the New Maturity Model


The new model defines five levels of maturity. It incorporates distributed systems alongside the mainframe and recognizes the new workloads, processes and challenges that will be encountered.
  1. Ad-hoc: The mainframe runs core systems and applications; these represent the traditional mainframe workloads and the green-screen approach to mainframe computing.
  2. Technology-centric: An advanced mainframe is focused on increasing volumes, higher capacity and complex workload and transaction processing while keeping a close watch on MIPS consumption.
  3. Internal services-centric: The focus is on mainframe-based services through a service delivery approach that strives to meet internal service level agreements (SLAs).
  4. External services-centric: Mainframe and non-mainframe systems interoperate through a services approach that encompasses end-user expectations and tracks external SLAs.
  5. Business revenue: Business needs and end-user experience are addressed through interoperability with cloud and mobile systems and real-time analytics to support revenue initiatives.
At each level the model identifies the following maturity categories:
  1. Application Technology: Core hardware and software, tools for interacting with mainframe applications
  2. Mainframe Attributes: View of mainframe from outside its core group, management of mainframe
  3. Culture: Interaction of the different technology disciplines and teams
  4. Performance Technology: Tools to ensure applications meet end-user performance expectations
  5. Process: New processes to resolve complex application performance problems
Adopting the new maturity model will be a gradual process, and most mainframe shops will find themselves straddling multiple levels for some time. They may be at the higher levels in terms of technology while remaining at a low level in terms of culture or process. The culture gap on both sides, however, needs to be addressed soon.

Alan Radding is a Newton, Mass.-based freelance writer specializing in business and technology. Over the years his writing has appeared in a wide range of publications including the New York Times, CFO Magazine, CIO Magazine and Information Week. He can be reached through his website, http://technologywriter.com.

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