Tag Archives: Mainframe

Big Data: Is the zSeries Mainframe A Viable Platform?

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Noting that ~80% of global corporate data is still managed by IBM Mainframes, doesn’t it make sense that processing this mission critical data should remain local, whenever practicable and pragmatic?

Industry Analyst’s estimate that 90%+ of existing IT budget expenditure is expended on the maintenance of existing applications and their supporting infrastructure. A significant factor is the siloed, duplicated and complex nature of these existing IT environments. Repeating this often unnecessary data duplication and processing for big data implementations will only exacerbate this significant TCO expenditure. Therefore it is of primary importance to consider big data from a strategic rather than a purely expedient tactical perspective. Put another way, if big data could be accessed and processed by the incumbent IBM Mainframe environment, why create another silo environment, requiring more servers, storage, software and associated maintenance expenditure?

It is estimated that each and every day another ~2.5 Exabyte’s (2.5 quintillion bytes) of data is created, meaning that ~90% of electronic data stored, has been created in the last two years alone. This data comes from numerous sources, largely Internet and mobile telephony based, including social media sources, digital pictures and videos, financial transaction records, cell phone generated, naming but a few.

Industry Analyst’s estimate that only ~1% of global data is currently analysed, leaving massive scope for growth in this functional area, namely big data analytics. Obviously this scope dictates exponential and arguably uncontrolled growth in deployment of big data analytics solutions, generating significant risk that big data projects will lack management oversight, spiralling out of control from a cost viewpoint.

It therefore follows that big data initiatives require careful and strategic planning, not only for short-term immediate requirements, but also for future big data projects that can already be perceived and forecasted. Moreover, in addition, there needs to be a strategic, scalable, cost efficient and secure infrastructure in place, managing the interrelationship and interdependencies, between mission critical data stored on the IBM Mainframe and big data being created from Internet and mobile technologies.

Without such a diligent and structured management framework, IT infrastructure expenditure costs (TCO) will increase, efficiency reduce, with the inevitable consequence of siloed environments, with duplication of resources, namely servers, software, storage, et al. As always, we must always apply lessons learned from past experiences to avoid these inefficiencies.

Hadoop is seemingly the big data buzzword, being an open source software framework for storing and processing big data in a distributed environment on large clusters of commodity hardware. Ultimately Hadoop delivers two primary functions, massive data storage and faster in memory I/O processing.

In conclusion, the underlying question remains, can mission critical IBM Mainframe data be “coupled” with big data, typically originating from Internet and mobile platforms, to deliver an integrated single image view of customer and/or product data, for business benefit?

IBM offers an integrated solution, namely the zEnterprise Analytics System (I.E. 9700, 9710), comprising hardware (E.g. z196/zEC12 or z114/zBC 12 Server plus DS8870 Disk) and software (E.g. Optimized z/OS software stack), combined with optional services. Primarily data analytics is delivered by the IBM DB2 Analytics Accelerator solution, incorporating Netezza 1000 product function, allowing for intelligent and rapid in-memory data analytics via the DB2 RDBMS. Therefore existing zSeries Mainframe customers can supplement their current IBM Mainframe infrastructure with the IBM DB2 Analytics Accelerator solution, while the realm of possibility exists for a zSeries Mainframe to be deployed for new workloads, via the zEnterprise Analytics System.

Resource and cost efficiencies are delivered by combining z/OS and Linux on zEnterprise solutions. Data transfer is reduced by keeping data analytics in the same environment as the mission critical source data (I.E. z/OS) using hypersockets to process the data between the IBM z/OS and Linux on zEnterprise systems. Overall TCO efficiencies are delivered by optimizing lower cost Linux on zEnterprise systems resources, where for Sub Capacity z/OS customers, no software charges will be incurred for associated CPU processing. Therefore leveraging from existing zEnterprise infrastructure resources, including people and processes to deploy and support expanding data analytics requirements.

zSeries Mainframe big data analytics solutions, whether via the packaged zEnterprise Analytics System or via the IBM DB2 Analytics solution deliver benefits including:

  • Optimized I/O Processing: Reducing the complexity and cost of data storage and associated processing by bringing data transformation and analytic processes to the data origin (I.E. zSeries Mainframe)
  • Enterprise Wide Data Availability: Safeguarding operational data accessibility to many users in a timely and cost efficient manner without impacting core business processes
  • Near Real Time Data Processing: Delivering near real time operational analytics with minimal latency and superior Quality of Service (QoS) attributes (I.E. RAS – Reliability, Availability, Serviceability)

Syncsort also provide their DMX-h ETL solution to integrate IBM mainframe data with Hadoop technologies. Syncsort DMX-h ETL incorporates a library of Use Case Accelerators to implement common ETL tasks including Mainframe data access, change data capture (CDC), joins, web log aggregations, et al. Implementing a more traditional ETL approach, offloading big data batch workload from the Mainframe to Hadoop platforms, reducing Mainframe MIPS accordingly. Obviously ETL solutions have a long-term history, typically associated with Business Intelligence, Data Warehouse, et al. One must draw one’s own conclusions as to whether ETL solutions contribute to the complexity and cost of managing mission critical business data…

From a business viewpoint, big data analytics delivers benefits, including but not limited to:

  • Optimized & Faster Decision Making: Performing real time analysis of customer transaction and activity data, feedback (E.g. survey and experience) data, et al, can dramatically reduce customer attrition, maintaining existing customer loyalty, applying these lessons learned for attracting new customers.
  • New Products & Services: Customer’s and associated market research have always provided valuable insight into driving innovation, but these traditional processes are time consuming and error prone. Rapidly analysing real life customer data from Internet and mobile sources, delivers an opportunity to offer a new product and/or service, seemingly specialized to their personal individual requirements.
  • Cost Reduction: Performed well, clearly big data analytics can deliver significant cost reduction for the business, reducing product/service development time, while retaining existing customers and attracting new customers. However, done badly, data analytics could be a significant drain on the IT expenditure budget

As always, the zSeries Mainframe delivers an integrated, scalable, secure and cost efficient solution for big data initiatives, even Hadoop, typically perceived as a Distributed Systems solution. Without doubt, big data solutions will be implemented by each and every major global company in the short-term, while pragmatic and careful planning will reduce the associated IT implementation and administration cost. With a legacy of several decades or more delivering enterprise wide solutions, arguably seasoned IBM Mainframe personnel are ideally placed to participate in the design and delivery of big data analytics projects!

Revisiting The zSeries Mainframe Storage Hierarchy

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Recommendation: The next time you perform a zSeries Mainframe server upgrade, consider adding Flash Express cards, for an extra 1.4-5.6 TB of memory speed storage. Similarly, the next time you perform a zSeries Mainframe DASD subsystem upgrade, consider adding as much SSD (flash memory) capability that you can afford and justify. Both upgrades will deliver significant performance and business benefits, arguably for minimal cost, when considered as a several year TCO investment.

Conceptually the zSeries Mainframe storage hierarchy has comprised the same layers for many decades, while performance and capacity attributes have dramatically increased over time. Although System/390 introduced the concept of Expanded Storage (I.E. Hiperspace, Data Space) in 1990 and there have been various implementations of SSD (E.g. StorageTek 4080), the ability to transparently implement significant capacity memory layers has only recently become possible.

Let’s not forget, the closer data is to that most precious and expensive of resources, namely CPU, the faster it will process. When revisiting the traditional storage hierarchy, we can now consider two new layers, namely Flash Express and Solid State Drive (SSD):

zSeries Storage Hierarchy

I have previously written about the Flash Express layer. Flash Express is a new memory layer within the zSeries Mainframe storage hierarchy, which can be considered as either a Solid State Drive (SSD) or Storage Class Memory (SCM) technology. Flash Express is integrated on PCI Express attached RAID 10 Cards, packaged as a two card pair, each with a 1.4 TB capacity per mirrored card pair. A maximum of 4 card pairs can be configured, delivering up to 5.6 TB of memory capacity, assigned to LPAR resources, just like main memory.

The simplest function to benefit from Flash Express memory would be SVC dump processing, substantially reducing dump capture time.

Flash Express can also be deployed to replace z/OS disk paging, substantially reducing the response time associated (I.E. ~5-20 μs vs. ~10 ms). The benefit for z/OS paging is not the replacement of memory paging, but replacing disk paging with Flash Express storage. Flash Express is suitable for workloads that can tolerate paging, but will not benefit workloads that cannot tolerate paging activity. The fundamental z/OS design for Flash Express memory will not completely remove any virtual storage constraints created by a paging spike, although a modicum of scalability relief is expected due to the faster I/O associated with Flash Express memory.

In conjunction with Flash Express, there were advancements in the Real Storage Management (RSM) function, including pageable 1MB Large Page Support. Large Pages (1MB) deliver benefit, with increased performance, decreasing the number of Translation Lookaside Buffer (TLB) misses that an application incurs, reducing time when converting virtual addresses into physical addresses and reduced real storage usage to maintain DAT structures. The use of Large Pages typically deliver Internal Throughput Rate (ITR) performance benefits of ~1% for IMS, ~3% for DB2 and ~5% for Java workloads.

Although SSD (flash) storage might have been selectively deployed in the zSeries Mainframe Data Centre for the last 5 years or so, the ever increasing requirement for increased Quality of Service (QoS) in terms of data availability and ultra-fast transaction response times dictate the increased usage of SSD architectures. Entire DASD subsystems can be built upon SSD technologies, or more likely, hybrid subsystems, containing both SSD and traditional HDD technologies. This storage subsystem evolution allows organizations to gain significant competitive advantages, delivering new services for existing and more importantly, new customers alike.

Using SSD disk subsystems, overcomes the limitations of traditional spinning hard disk drives. However, not every enterprise application needs this ultra-high performance; since flash storage still costs more than spinning drives for the same capacity, organizations must be mindful of expenditure and now much flash memory (SSD) they deploy; as always, flexibility is key.

Complete or hybrid SSD I/O subsystems deliver performance and economic advantages for your mission critical business environment:

  • Green Data Centre: ~25-60% energy reduction (flash memory vs. spinning disk)
  • Data Centre Space: ~20-40% smaller footprint (memory cards vs. Hard Disk Drives)
  • Optimal Performance: Consistent ~1-3 ms access (Hard Disk Drives @ ~10 ms)

The utopia is for a self-tuning disk subsystem, automatically redirecting I/O between SSD and HDD, based on file performance and overridden, as and when required, by storage policies. Whether EMC, HDS (HP OEM) or IBM, this self-tuning ability is evolving, while each disk vendor has their own implementation. However, whatever your choice of disk subsystem, the ability to incorporate SSD into your storage hierarchy, either full or partial is evident.

In conclusion, ~25 years ago, the zSeries Mainframe user benefitted from faster performance via System/390 Expanded Storage and disk subsystems with cache and DASD Fast Write memory buffers. The cost of such memory storage was a major consideration then, but with good I/O tuning disciplines, the savvy zSeries Mainframe user benefitted from these technology advancements. Flash Express and SSD deliver the potential to deliver increased performance, for a relatively low cost, and now is the time to embrace these technologies. Ignore the storage hierarchy at your peril and as I previously documented, optimal I/O performance always delivers significant benefit.

zLearning – Social (Face-to-Face) Networking

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In The UK, it’s that time of the year again where a certain subset of us more mature folks dust down some of our costumes and prepare for the upcoming event.  Allegedly, I’m not sure how true this is, some of us look better in costume!  No, it’s not Halloween, but the UK GSE Annual Conference!  This year, 2014, marks 20 years and the 21st offering of this annual event.  A lot has changed in those 20 years…

In the early 1990’s, I can remember attending GSE user group meetings with many tens if not one hundred plus attendees, the majority being from customer installations.  Not so long ago, I also recall such meetings where there were less than 10 attendees, most of those from vendors.  So, congratulations to all of those hard working UK GSE representatives that give their time, effort, passion and skill to promoting and supporting this event, where the annual UK GSE conference now attracts several hundred attendees.  Maybe the number of vendor attendees now outnumbers those from customer installations, but the realm of possibility exists.

Although it might not be obvious, this arguably unique annual UK zSeries Mainframe user conference is the best if not only multi-faceted education forum for UK based Mainframe users.  With many technical streams, real-life experiences from customer presentations and latest product updates from vendors, perhaps UK GSE is the best “zLearning” opportunity of the year?  If so, I really hope UK zSeries Mainframe user personnel continue to support this great event and attendee numbers keep growing.  Personally, I would like to see user presentations dominate the conference and this can only happen if user personnel support the event and convince their Management Team that they should attend and present.

Moreover, arguably the greatest quality and attribute of the annual UK GSE conference is the ability for face-to-face networking, interacting with industry peers that may have faced and resolved some of the challenges on your to-do list.  For sure, a lot can be achieved with Social Media resources, Facebook, LinkedIn, Twitter, et al; but we should never lose sight of that face-to-face interaction.

A recent noteworthy addition to the UK GSE conference is the welcome attendance from University Students, who are the future and we hope they embrace the zSeries Mainframe platform and forge a career accordingly.  Who knows, whether a vendor or a customer, perhaps you might find a welcome addition to your workforce from these talented students?

What will the next 20 years bring?  I hope that attendee numbers are always measured in the hundreds and if there are ~100 Mainframe customers in The UK and 2 personnel from the majority of those customers attended, there must be a great possibility of ~30-40 user presentations per conference.  I also wonder how many students that attend the UK GSE conference, actually go onto find a job and start their career in the zSeries Mainframe world.  I think that might be one of the most noteworthy and legacy achievements of this great UK GSE event and perhaps one worth documenting.  Now there’s a good use of Social Media, a resource where folks can post something like “The UK GSE conference helped me get my first IT (Mainframe) job”.  Enjoy the forthcoming 2014 conference.

IFL – A Cost Efficient zSeries Platform?

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In September 2000, IBM introduced the Integrated Facility for Linux (IFL) processor, a specialty engine for and some might say dedicated to running the Linux Operating System.  At the time of this announcement, companion software named S/390 Virtual Image Facility for Linux was introduced to assist in the rapid deployment of IFL configurations, especially for non-Mainframe personnel.  However, this product was quickly discontinued, in favour of the standard z/VM Operating System, which is not difficult to learn and can accommodate hundreds if not thousands of zLinux images.

Today, the IFL is still a processor dedicated to Linux workloads on IBM System z servers.  The IFL is supported by z/VM virtualization and the Linux operating system.  The IFL cannot run other IBM operating systems.  The competitively priced IFL processor is a CPU capacity enabler, exclusively for Linux workloads.  Linux deployment (I.E. SUSE & Red Hat) on IFL’s can reduce expenses in the areas of operational efforts, energy, floor space and especially software.

The IFL provides the following functions and benefits:

  • The IBM Enterprise Linux Server is a dedicated System z Linux server, comprised of only IFL processors
  • No additional IBM software charges for traditional (E.g. z/OS, CICS, DB2, WebSphere, et al) environment
  • Performance improvement for Linux workloads with each successive generation of IFL and System z technology
  • Linux workload on the IFL does not result in increased IBM software charges for traditional System z operating systems and middleware
  • Same functionality as a General Purpose processor on a System z server
  • HiperSockets can be used for communication between Linux images, or Linux and other operating system images on the same System z system
  • z/VM virtualization and most IBM Linux middleware products, plus most vendor software products are priced per processor (core) according to the System z IBM International Program License Agreement (IPLA).  IPLA products have a one-time-charge (OTC) and an annual (optional) maintenance charge, called Subscription & Support
  • Supported by the current z/VM virtualization and IBM Wave for z/VM software versions
  • Always a full capacity processor, independent of the capacity of the other processors in the server
  • Orderable as a System z hardware feature. The number of orderable IFL features varies by the server model and configuration
  • Designed to operate asynchronously with other General Purpose processors
  • Managed by PR/SM in logical partition with dedicated or shared processors. The implementation of an IFL requires a Logical Partition (LPAR) definition, where following normal LPAR activation procedure, LPAR defined with an IFL cannot be shared with a general purpose processor.

There will always be the debate as to which processor and associated server type (E.g. x86, POWER, SPARC) is the most cost efficient, but there is no doubt that the ability to accommodate hundreds if not thousands of zLinux instances in one zServer environmental (E.g. Power, Cooling, Floor Space, et al) friendly footprint, with software pricing per core is worthy of consideration.

Adoption for zLinux has been steady and especially in the emerging territories where it’s not unusual for zSeries deployments to be totally zLinux (I.E. IBM Enterprise Linux Server) based.  Moreover, the majority of large and traditional IBM Mainframe users (I.E. z/OS) have installed at least one IFL, if only to evaluate the z/VM and zLinux offering.  Many have deployed the IFL and associated zLinux solution for business requirements.

Therefore, if one of the major cost benefit features of IFL is optimized software costs; can the IFL processor be considered for other workloads, originating from the traditional zSeries (I.E. z/OS) environments?

Proximal Systems Corporation (PSC) is a company with a solution that transparently offloads data processing from IBM Mainframes to Distributed Systems, with an objective of reducing software cost, while maintaining or improving performance.  The company name is derived from the concept of bringing disparate computing systems into close proximity, functionally speaking, providing totally seamless and transparent interoperability.  The result is a unified computing complex within which various tasks can be easily migrated between systems to their most cost efficient operating environment, while still being able to interoperate as if they were all hosted together on the same system.

The PSC Proxy Coupling Technology allows for a CPU orientated task to be offloaded from one system to another by means of an associated proxy task, which has an identical interface as the task to be offloaded, but delegates the majority of the processing to an offloaded task on another system.  The primary objective of this function are for the cost savings and/or performance improvements that might be delivered by migrating tasks to systems that are able to execute those tasks more efficiently.

The fact that the proxy task maintains the same interface as the application being replaced is crucial; as many past Mainframe migration projects have failed due to insurmountable interoperability problems between the Mainframe and Distributed Systems servers (I.E. Windows, Linux, UNIX, et al).  Proxy Coupling Technology offers a solution to this long-standing challenge.  In theory, this allows for the transparent offload of a traditional z/OS workload (E.g. Sort) from General Purpose (GP) processors, to a less expensive (E.g. IFL) alternative…

In the first instance, the Proxy Coupling Technology offloads General Purpose CPU workload associated with the z/OS sort (I.E. CA Sort, DFSORT, Syncsort) function, to another platform (E.g. IFL).  For IFL based implementations, HyperScokets are utilized to transfer data at memory speeds from the z/OS task to zLinux on the IFL, where the sort operation completes, while the resulting z/OS task and associated data are maintained, as per normal.  From an IFL viewpoint, Ahlsort software performs the sort operation, being a sort solution that maintains compatibility with the majority of z/OS sort function (I.E. Control Card Syntax).  Therefore, this is a transparent implementation, where the only consideration is how much CPU capacity is required for the offload function (E.g. IFL, x86).  The benefits are reduced z/OS MSU usage for the sort function, which can be quite significant, as most business data (E.g. Database Offloads, Customer Orientated, et al) is sorted on a daily if not more frequent basis.

Just as IBM introduced the zAAP on zIIP capability, which allowed some customers to more easily justify a specialty engine (I.E. zIIP), combining workloads to exploit the full capability of the specialty engine; in theory the same ethos applies with the Proxy Coupling Technology.  For the avoidance of doubt, workloads that can be processed on an IFL, such as z/OS sort tasks, can assist in delivering higher Return On Investment (ROI) levels for the IFL, for example:

  • Reduced z/OS WLC MSU usage (I.E. Sort function offload) and associated software costs savings
  • IFL processors run at Full Speed and do not add to traditional workload (I.E. z/OS) software costs
  • Utilize any spare IFL CPU resource not used, releasing General Purpose CPU resource for other work

In conclusion, the Proxy Coupling Technology offers a proposition that is similar to the IBM philosophy of reducing z/OS software costs via specialty engines.  Seemingly to date, primarily only the zIIP and zAAP specialty engines were available to optimize CPU usage for z/OS workloads.  Offloading CPU cycles and thus MSU workload to IFL makes sense, utilizing a cost efficient and indeed a full power CPU engine, where for cost reasons, maybe the majority of z/OS customers don’t deploy the “highest” derivative of General Purpose CPU engine available to them.  On the face of it, the realm of possibility exists for other workloads to benefit from z/OS to IFL CPU offload, following sort, which seems to make sense as the first workload to utilize this solution.

Apple Style Meets IBM Substance

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It was the early 1980’s when IBM first announced the Personal Computer (PC), a major breakthrough for delivering affordable and practical computing into the home.  One of the primary features of this computing evolution was the “open architecture” of the PC, built from off-the-shelf and commodity components.  Of course, we all know that around this time, DOS became MS-DOS via Bill Gates and Microsoft, where the rest as they say, is history!

At this time the IBM Mainframe (1964) had nearly 2 decades longevity and was already proving a scalable, secure and reliable platform.  So here we are, some 3 decades later, where Apple and IBM have announced a Global Partnership to Transform Enterprise Mobility.

Whatever your opinion of Apple technology, in the last decade or so they have undoubtedly delivered slick design and style for mobile devices, namely the smartphone and tablet.  Therefore whether the Enterprise accept the premise or not, Bring Your Own Device (BYOD) is inevitable, where employees expect to use their personal devices in the workplace.

IBM have continued to be a dominant force in the Enterprise market, whether with Mainframe technology or not, while establishing a credible presence in the Cloud market space.  As always the world of IT is constantly changing and even though IBM sold its PC business to Lenovo in 2004; some 10 years later, as part of the exclusive IBM MobileFirst for iOS agreement, IBM will sell iPhones and iPads with industry-specific solutions to business clients worldwide.

So what role if any will the IBM zSeries platform play in this Apple deal?  As always, the zSeries platform will deliver enterprise scalability and strength for Security, Database and Messaging integration, but beyond these features, I’m not so sure.  Of course, from a data presentation viewpoint, nothing changes, iOS integration and the ability to present Mainframe originated data remains forever thus for Apple and indeed all other mobile devices.  Similarly from a business transaction viewpoint, the zSeries platform participates in the delivery of mobile support, where from an IBM technology viewpoint, the Worklight solution is one example of an end-to-end integrated development studio software product.

Despite the obvious benefits for Apple, gaining access to the Enterprise via IBM technology and their customer base, and for IBM, delivering the market leading mobile technology into their customer base, what does this mean for the Enterprise?

Business as usual mostly, but Identity & Access Management (IAM) would appear to be a significant challenge.  Firstly, rightly or wrongly, most people don’t consider Apple software to have any security exposures, as the market place for iOS security solutions (E.g. Anti-Virus, Malware, zero day exploits, et al) is limited?  However, one might ponder why the Windows Operating System became such a target for the hacker.  Said hacker might be an opportunist, just because they can, or something more sinister, trying to gain government or business secrets.  So, if the Apple smartphone and tablet devices become ubiquitous if not de facto in the Enterprise, how long will it be before security exposures for iOS and related apps become common place?

I’m open-minded about BYOD (or am I)?  My heart tells me, yes, let the workers use their own device in the workplace, but my head tells me, no way!  Generally for technology decisions, my head always wins.  In this instance, I don’t think my head has a chance; overwhelming company worker desire to use their own mobile device in the workplace, whether iOS, Android, Java ME, Windows Phone, Blackberry, et al, will win out.  If this is the case, this is perhaps where the maturity and reliability of the IBM zSeries Mainframe can assist.

Therefore, at least for Identity & Access Management (IAM), secure access to the most valuable resource within an organization, the data itself via the zSeries server makes sense.  Whether this is via two if not several factor authentication remains to be seen.  However, I’m much more comfortable with an IAM solution that leverages from a Mainframe External Security Manager (ESM), namely ACF2, RACF or TopSecret, as opposed to a universal log-in via a Social Media web site, such as Facebook.  Just because you can log into an Enterprise and arguably mission critical CRM application, such as Salesforce via Facebook Authentication, doesn’t necessarily mean you should…

The IBM Mainframe: Just Another Node On The IP Network!

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With the introduction of MVS/ESA Version 4.3 in 1993, the IBM Mainframe included the major foundations for meaningful Distributed Systems connectivity, including the first steps of POSIX compliance via OpenEdition functionality.  However, even before this timeframe, the TCP/IP protocol was available in the first release of MVS/ESA Version 4 (4.1), although in a very limited fashion.  In this instance, MVS was benefitting from the path already trodden by the VM Operating System and the TCP for VM software product.  Put another way, even when TCP/IP was in its early stages, being deployed and evolved in universities and scientific laboratories (E.g. CERN), its foundation was being embedded into the IBM Mainframe.

Early IBM Mainframe TCP/IP usage allowed for RS/6000 (AIX) connectivity, LAN integration via Novell NetWare, typically via the 3172 Interconnect Controller, Sockets Interface (E.g. CICS), et al.  In 1994, IBM introduced the Open Systems Adapter (OSA) processor feature for S/390 Parallel Enterprise Servers.  The OSA provided native Open Systems connectivity to the Local Area Network (LAN), directly via the Mainframe processor.  The OSA feature supported the Fiber Distributed Data Interface (FDDI), Token-Ring & Ethernet LANs, arguably making the 3172 controller obsolete.

So, since the early-mid 1990’s, even before pervasive usage of the Internet, the Mainframe was already a fully functioning and efficient user of IP networking.

How is the TCP/IP function being utilized by the IBM Mainframe today?

TCP/IP on z/OS supports all of the well-known server and client applications.  The TCP/IP started task is the engine that drives all IP-based activity on z/OS.  Even though z/OS is an EBCDIC host, communication with ASCII-based IP applications is seamless.

IP applications running on z/OS use a resolver configuration file for environmental values.  Locating a resolver configuration file is somewhat complicated by the dual operating system nature of z/OS (UNIX and MVS).  Nearly each and every z/OS customer deploys the following core TCP/IP services:

TCP/IP Daemon: The single entity that handles, and is required for, all IP-based communications in a z/OS environment is the TCP/IP daemon itself.  The TCP/IP daemon implements the IP protocol stack and runs a huge number of IP applications to the same specifications as any other operating system.

TCP/IP Profile: Is loaded by TCP/IP when started.  If a change needs to be made to the TCP/IP configuration after it has been started, TCP/IP can be made to reload the profile dynamically (or read a new profile altogether).

FTP Server: Like some other IP applications, FTP is actually a z/OS UNIX System Services (USS) application.  It can be started within an MVS environment, but it does not remain active in z/OS.  It immediately forks itself into the z/OS UNIX environment and tells the parent task to kill itself.

Telnet Daemon: There are two telnet servers available in the z/OS operating environment.  One is the TN3270 server, which supports line mode telnet, but it is seldom used for just that.  Instead, it is primarily used to support the TN3270 Enhanced protocol. The other telnet server is a line mode server only, referred to as the z/OS UNIX Telnet server (otelnetd).

Many IBM and ISV software products exploit IP and USS functionality, most typically WebSphere (MQ).

Whether UNIX System Services (USS) or TCP/IP usage, the convergence of the IBM Mainframe and UNIX technologies arguably became mandatory with the deployment of TCP/IP on the IBM Mainframe.  Obviously the technical personnel that support these different platforms have their own viewpoint as to which platform might be the best, but that is somewhat of an arbitrary point.  However, what is absolutely certain is recognition of how data is stored and secured in a UNIX environment and indeed the z/OS (MVS) specific environment, originally named MVS OpenEdition, but now commonly referred to as OMVS.

There are fundamental differences too numerous to mention when comparing the User and File management policies and processes, when comparing the security and data access lifecycle intricacies of z/OS and UNIX.  So what you might say!  This might be a cursory and lax attitude, as business critical data is probably being stored in OMVS file systems, if only for FTP purposes, but more than likely for other more pervasive and user based access (E.g. Database, Messaging, Data Mining, Data Exchange, et al).

So, which technical party is managing the security of Unix System Services (USS) file systems for the OMVS Mainframe deployment?  Is it the Mainframe Systems Programmer, the Unix System Admin or the Mainframe Security Team, or somebody else?  To date, some people might have thought it didn’t matter, but of course, seasoned security professionals knew that this was never the case.  However, the migration to z/OS 2.1 is a tangible juncture for each and every IBM Mainframe installation to review their USS and thus OMVS security deployment.  Why?

The BPX.DEFAULT.USER facility was introduced with OS/390 2.4 and was a commonly used process for implementing USS (OMVS) security.  However, with z/OS 2.1, the BPX.DEFAULT.USER facility is withdrawn, meaning that the Mainframe user must perform some migration actions.  IBM provide some generic assistance with this challenge via APAR OA42554 and APAR OA37164.  However, maybe this is an ideal juncture to perform a thorough review of USS (OMVS) security, vis-à-vis a comprehensive and dispassionate audit, highlighting issues, implementing standards and securing exposures.  For example, use of UID(0) must be eradicated and certainly no human being should be allocated such privileges.

There are some useful guidelines available from security specialists such as Vanguard, where the process can be simplified using their Identity & Access Management (IAM) toolset.  Similarly, recent user conferences have included presentations on this subject matter.

In conclusion, the IBM Mainframe can be classified as just another node on the IP (TCP/IP) network.  However, as always, no matter how secure the Mainframe platform might be, the biggest threat is typically the human being, and for USS, the migration to z/OS 2.1 forces us to review OMVS security settings.  Therefore, let’s do a good job and eradicate any security exposures we might have inadvertently implemented over the years.  As we all know, passing an external security audit process doesn’t necessarily mean our IT systems and processes are secure, while sometimes the internal security people are better qualified or more knowledgeable than external auditors.  Arguably most external auditors will do a good job of auditing UNIX platforms, yet their Mainframe knowledge and abilities are typically limited.  It is therefore somewhat of a paradox that in this particular area of z/OS USS, the typical UNIX exposures are not highlighted in the typical Mainframe security audit process…

One must draw one’s own conclusions as to the merits of engaging 3rd Mainframe security specialists to perform such an audit, coinciding with this z/OS 2.1 migration activity, safeguarding that OMVS security and processes are as good and secure as they can be.  Put another way, why wouldn’t a Mainframe organization go that extra mile to safeguard their most valuable of assets, namely business critical data, engaging a 3rd party specialist to review and provide guidance on this subject matter.

Are You Ready For z/OS Mobile Workload Pricing (MWP)?

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Recently IBM announced Mobile Workload Pricing (MWP) for z/OS which can minimize the impact of mobile workloads on Sub-Capacity license charges, delivering optimized pricing for System z environments extending their workloads to incorporate mobile devices.

MWP only applies to Mainframe customers deploying a zEC12 or zBC12 in their enterprise, as per the AWLC or AEWLC (AKA Advanced/Entry Workload License Charges) metric; MWP is also extended if a zEC12 or zBC12 enterprise is deploying a z196 or z114 via the AWLC or AEWLC metric.

The primary consideration for MWP is determining how a Mainframe customer can comply with the tracking requirements for mobile workloads.  On the plus side, MWP does not require an isolation of mobile workload transactions in separate LPARs, using enhanced reporting for software pricing.  This is a major step forward when compared with Integrated Workload Pricing (IWP), which ideally requires large LPAR container structures, minimizing costs for WebSphere workloads, applying to the CICS, IMS and WebSphere MLC software products.  Conversely, MWP includes DB2 in the list of eligible software products for cost reduction.

If a Mainframe customer is eligible for MWP pricing they will then need to utilize the Mobile Workload Reporting Tool (MWRT), which is analogous to the original Sub-Capacity Reporting Tool (SCRT).  This is an either/or situation, the Mainframe customer only submits MCRT reports to IBM if they’re MWP eligible, or the status quo remains, where non-MWP Mainframe customers continue to submit SCRT reports.

The Mainframe customer must track and report General Purpose (GP) CPU time for mobile transactions, reporting those values in a pre-defined format to IBM each month to benefit from MWP.  MWRT utilizes reported mobile transaction data to adjust the Rolling 4 Hour Average (R4HA) Sub-Capacity software eligible MSUs, with LPAR granularity.  Optimizing mobile transactions impact for peak LPAR MSU values delivers benefit when higher mobile transaction volumes generate MSU resource usage peaks (Workload Spikes).

MWRT calculates the R4HA for mobile transaction GP MSU resource usage, subtracting 60% of those values from the traditional Sub-Capacity software eligible MSU metric, with LPAR granularity, for each and every reporting hour.  The software program values for the same hour are aggregated for all Sub-Capacity eligible LPARs, deriving an adjusted Sub-Capacity value for each reporting hour.  Therefore MWRT determines the billable MSU peak for a given MLC software program on a CPC using the adjusted MSU values.

Most committed zSeries Mainframe customers will be deploying CICS, DB2 and WebSphere software, while IT trends dictate that mobile device usage (I.E. Smartphone, Tablet, et al) is increasing.  Therefore most z/OS applications that require such mobile access have evolved accordingly over time.  Therefore it seems to be one of those “No Brainer” type scenarios, where the Mainframe user should plan to benefit from MWP, either as they upgrade to the latest zSeries technology, namely zEC12 or zBC12, or immediately if already deploying a zEC12 or zBC12 server.

The only minor consideration is a requirement for the zEC12 or zBC12 customer to engage their local IBM account team, to determine what data they need to report on mobile transactions for MWP consideration.  This one off task will deliver optimized WLC pricing forever more.

Of course IBM are encouraging customers to consider the Mainframe for new applications, driven by mobile transaction requirements.  Equally, there is no reason why longer term Mainframe customers can’t benefit from MWP, benefitting from reduced MLC costs, a major consideration of Mainframe TCO.

z/OS Soft Capping: Balancing Cost & Performance

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Historically each and every LPAR was assigned a Relative Weight value; where a more meaningful description would be the initial processing weight. This relative weight value is used to determine which LPAR gains access to resources, where multiple LPARs are competing for the same resource. Being unit-less is one minor challenge of the relative weight value, meaning that it has no explicit CPU capacity or resource value. Typically installations would use a simple multiple of ten metric, most likely 1000, and allocate weights accordingly (E.g. 600=60%, 300=30%, 10=10%, et al). Therefore during periods of resource contention, PR/SM would allocate resources to the requisite LPAR, based upon its relative weight.

Using relative weight to classify all LPARs as equal, at least from a generic class viewpoint, does have some considerations; primarily differentiating between Production and Non-Production workloads. Restricting a workload to its relative weight share of resources is known as Hard Capping. This setting is typically used to restrict Non-Production (E.g. Test) environments to their allocated resource and is also useful for cost control (E.g. Outsourcers), knowing that the LPAR will never consume more than its allocated relative weight allowance.

Hard Capping behaviour changes dependent on the use of the HiperDispatch setting. When HiperDispatch is not chosen, capping is performed at the Logical CP level, where the goal is for each logical CP to receive its relative CP share, based on the relative weight setting. When HiperDispatch is active, vertical as opposed to horizontal CPU management applies. So, a High categorization dictates capping at 100% of the logical CP, whereas a Medium or Low setting allows for resource sharing based on a relative weight per CP basis.

The Intelligent Resource Director (IRD) function provides more advanced relative weight management, automating management of CPU resources and a subset of I/O resources. Workload Manager (WLM) manages physical CPU resource across z/OS images within an LPAR cluster based on service class goals. IRD is implemented as a collaboration between the WLM function and the PR/SM Logical Partitioning (LPAR) hypervisor:

  • Logical CP Management: dynamically allocating logical processors (E.g. Vary On-Line/Off-Line)
  • Relative Weight Management: dynamically redistributing CPU resource as per LPAR weights
  • CHPID Management: dynamically assigning logical channel paths between eligible LPARs

IRD optimizes resource usage, enabling WLM to deliver workload goals.

The use of relative weight in association with Hard Capping and/or IRD/WLM granularity has become somewhat limited for most Mainframe installations with the advent of Sub-Capacity pricing (I.E. MLC via SCRT/R4HA). Primarily because there is no direct correlation to manage CPU resource at a meaningful level, namely the MSU (vis-à-vis CPU MIPS) metric.

Defined Capacity (DC) provides Sub-Capacity CEC pricing by allowing definition of LPAR capacity with a granularity of 1 MSU. In conjunction with the WLM function, the Defined Capacity of an LPAR dictates whether Soft Capping is invoked or not. At this juncture, we should consider how and when WLM measures CPU resource usage and if and when Soft Capping is activated and deactivated:

WLM is responsible for taking MSU utilization samples for each LPAR in 10-second intervals. Every 5 minutes, WLM documents the highest observed MSU sample value from the 10-second interval samples. This process always keeps track of the past 48 updates taken for each LPAR. When the 49th reading is taken, the 1st reading is deleted, and so on. These 48 values continually represent a total of 5 minutes * 48 readings = 240 minutes or the past 4 hours (I.E. R4HA). WLM stores the average of these 48 values in the WLM control block RCT.RCTLACS. Each time RMF (or BMC CMF equivalent) creates a Type 70 record, the SMF70LAC field represents the average of all 48 MSU values for the respective LPAR a particular Type 70 record represents. Hence, we have the “Rolling 4 Hour Average”. RMF gets the value populated in SMF70LAC from RCT.RCTLACS at the time the record is created.

SCRT also uses the Type 70 field SMF70WLA to ensure that the values recorded in SMF70LAC do not exceed the maximum available MSU capacity assigned to an LPAR. If this ever happens (due to Soft Capping or otherwise) SCRT uses the value in SMF70WLA instead of SMF70LAC. Values in SMF70WLA represent the total capacity available to the LPAR.

We should also consider the two possibilities for MLC software payment (I.E. SCRT) based upon MSU resource usage. Quite simply, the MSU value passed for SCRT invoice consideration is the R4HA or the Defined Capacity, whichever is the lowest. Put another way; if the R4HA exceeds Defined Capacity, Soft Capping applies to the LPAR.

The primary disadvantage of Soft Capping is that the Defined Capacity setting is somewhat static; it is manually defined once, maybe several times a day for workloads with distinct characteristics (E.g. On-Line, Batch, et al), but dynamic DC management based upon inter-related LPAR behaviour is at best, evolving. The primary considerations for Soft Capping are:

  • An LPAR can only be managed via Soft Capping or Hard Capping; not both
  • DC rules only applies to General Purpose CP’s (Hard Capping for Specialty Engines is allowed)
  • An LPAR must be defined with shared CP’s (dedicated CP’s not allowed)
  • All LPAR Sub-Capacity eligible products have the same MSU capacity (I.E. DC)

Soft Capping is relatively simple to implement and typically generates MLC software costs savings, with minimal impact.

Group Capacity Limit (GCL) provides an extension to the Defined Capacity (DC) Soft Capping function. GCL allows an MSU limit for total usage of all group LPARs, with a granularity of 1 MSU. The primary considerations for GCL are:

  • Works with DC LPAR capacity settings
  • Target share does not exceed DC
  • Works with IRD
  • Multiple CEC groups allowed; but an LPAR may only be defined to one group
    An LPAR must be defined with shared CP’s, with WAIT COMPLETION = NO specification

It is possible to combine IRD weight management with the GCL function. Based on installation policy, IRD can modify the relative weight setting to redistribute capacity resource within an LPAR cluster.

However, IRD weight management is suspended when GCL is in effect, because LPAR resource entitlement within a capacity group can be (I.E. Pre zxC12) derived from the current weight. Hence the LPAR might get allocated an unacceptable low weight setting, generating a low GCL entitlement.

GCL also allows for MSU to be shared between LPARs in a group, where one LPAR would be a donator and another would be a receiver. Therefore the customer classifies their LPARs accordingly and when a high-priority LPAR requires additional MSU resource, it will be allocated from a lower priority LPAR, if available. This provides a modicum of flexibility, but by definition, peak workloads are not predictable and typically require a significantly higher amount of MSU for a short time period. Typically this requirement will not be satisfied with the GCL function.

Soft Capping techniques, either at the individual (DC) or group (GCL) level deliver cost saving benefit, but a fine granularity of management is required to balance cost saving versus associated performance considerations. The primary challenges associated with Soft Capping are its interactions with workload characteristics and an inability to dynamically manage MSU allocation, in-line with the R4HA. Put another way, the R4HA is derived from 48*5 Minute samples, whereas DC and GCL settings are typically defined on an infrequent (E.g. Monthly or longer) basis.

As z/OS evolves, further in-built function is available to manage MSU capacity. zSeries Capacity Provisioning Manager (CPM) is designed to simplify the management of temporary capacity, defined capacity and group capacity. The scope of z/OS Capacity Provisioning is to address capacity requirements for relatively short term workload fluctuations for which On/Off Capacity on Demand or Soft Capping changes are applicable. CPM is not a replacement for the customer derived Capacity Management process. Capacity Provisioning should not be used for providing additional capacity to systems that have Hard Capping (initial capping or absolute capping) defined.

With the introduction of z/OS 2.1, CPM functionality incorporates Soft Capping support via the DC and GCL functions. CPM functions from a set of installation defined policies and parameters, where the CPM server receives three types of input:

  • Domain Configuration: defines the CPCs and z/OS systems to be managed
  • Policy: contains the information as to which work is eligible, for which conditions and during which timeframes and capacity increases for constrained workloads
  • Parameter: contains environment descriptors (E.g. UNIX Environment, Installation Options, et al)

From a customer viewpoint, policy definition allows them to define the provision of CPU resource:

  • Date & Time: When capacity provisioning is allowed
  • Workload: Which service class qualifies for provisioning?
  • CPU Resource: How much additional MSU capacity can be allocated?

CPM provides more function when compared with Defined Capacity and Group Capacity Limit Soft Capping techniques. Therefore allowing for time schedules to be defined, workloads to be categorized and MSU resource to be allocated in a dynamic and granular manner.

A modicum of complexity exists when considering the arguably most important factor for CPM policy definition, namely the Performance Index (PI):

  • Activation: PI of service class periods must exceed the activation threshold for a specified duration, before the work is considered as eligible.
  • Deactivation: PI of service class periods must fall below the deactivation threshold for a specified duration, before the work is considered as ineligible.
  • Null: If no workload condition is specified a scheduled activation/deactivation is performed; with full capacity as specified in the rule scope, unconditionally at the start and end times of the time condition.

For workload based provisioning it is a necessary condition that the current system Performance Index exceeds the specified customer policy PI metric. One must draw one’s own conclusions regarding PI criteria settings, but to date, they’re largely based on arguably complex mathematical formulae, which perhaps is not practicable, especially from a simple management viewpoint.

With the requisite hardware (I.E. zxC12+) and Operating System levels (I.E. z/OS 1.13+), CPM provides extra functionality for the customer to implement granular Soft Capping techniques to balance cost and performance. When compared with Defined Capacity and Group Capacity Limit techniques, CPM delivers increased granularity for managing capacity dynamically, based on customer derived policies, recognizing time slots, workloads and MSU resource increases accordingly.

From a big picture viewpoint, without doubt, we must recognize the fundamental role that WLM plays in Soft Capping. Quite simply, the 48*5 Minute MSU resource samples dictate whether a workload will be eligible for Soft Capping or not and from a cumulative viewpoint, these MSU samples dictate the R4HA metric. Based on this observation, efficient and functional Soft Capping must be workload based (I.E. WLM Service Class), be dynamic and operational on a 24*7 basis, because workload peaks are never predictable, while balancing MSU resource accordingly. Of course, simplicity of implementation and management, supplemented by meaningful reporting is mandatory.

Once again, observing the 48*5 Minute MSU resource samples from a R4HA viewpoint, if a workload was to increase MSU usage by an average of 50% for 1 Hour (I.E. 12 Samples), and decrease MSU usage by an average of 20% for 2.5 Hours (I.E. 30 Samples), from an average viewpoint, the R4HA has remained static. Therefore an optimum Soft Capping technique needs to recognize WLM service class requirements, reacting in a timely manner, increasing and decreasing MSU usage, to safeguard workload performance for Time Critical workloads, while optimizing SCRT MLC cost.

zDynaCap delivers automated capacity balancing within CPCs, Capacity Groups or Groups of LPARs. Central to zDynaCap are the predefined balancing policies. Within these balancing policies, users define their MSU ranges of Groups and LPARs and also the priorities of the associated LPAR Workload. zDynaCap continually monitors overall usage and compares this to the available capacity and the user defined MSU balancing policies. For example, should a high priority workload on one LPAR not get enough capacity, while a low priority workload on another within the group gets too much capacity, available MSU capacity is distributed according to customer derived balancing policies. Only if there is no leftover capacity to be rescheduled within the defined Group, and if the high or medium priority workload will be slowed down, will zDynaCap add MSU.

With zDynaCap Capacity Balancing, available MSU capacity is balanced within LPAR groups, safeguarding that during peak time the mission critical workload is processed as per business expectations (E.g. SLA/KPI) for the lowest possible MLC cost.

In conclusion, given the significance of IBM MLC software (E.g. z/OS, CICS, DB2, IMS, WebSphere MQ, et al) costs, arguably every Mainframe environment should deploy a capping technique for cost optimization. Hard Capping might work for some, but in all likelihood, Soft Capping is the primary choice for most Mainframe environments. For sure, IBM have delivered several Soft Capping techniques, with varying levels of function and granularity, namely Defined Capacity, Group Capacity Limit (GCL) and the zSeries Capacity Provisioning Manager (CPM). It was forever thus and the ISV community exists because they specialize, architect and deliver specialized solutions and zDynaCap is such a solution, recognizing the fundamental rules of IBM Mainframe Soft Capping, namely the underlying WLM and R4HA foundation.

zIIP Into The Future: Mainframe Specialty Engines Evolution

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Sometimes we might lose sight that change can be evolutionary as opposed to revolutionary and this certainly applies to IBM Mainframe specialty engines, for example:

  • 1997: Internal Coupling Facility (ICF)
  • 2000: Integrated Facility for Linux (IFL)
  • 2004: System z Application Assist Processor (zAAP)
  • 2006: System z Integrated Information Processor (zIIP)

To assist with lower IBM software pricing, arguably the ICF offering became the de facto standard for a Mainframe user to be considered “actively coupled”.  Therefore deploying two or more eligible IBM Mainframes, physically attached via coupling links to a common Coupling Facility (I.E. ICF).

The Integrated Facility for Linux (IFL) is a processor dedicated to Linux workloads on IBM System z servers.  The IFL is supported by the z/VM virtualization software and the Linux operating system.  Most customers have at least dabbled into this technology, while some are using this technology extensively, primarily for distributed server consolidation.

Somehow the zAAP specialty engine has become the “black sheep” of the family where the current zEC12 and zBC12 are planned to be the last System z servers to offer support for zAAP specialty engine processors.

As of z/OS V1.11, functionality was delivered enabling zAAP eligible workloads to run on zIIP engines.  This function allowed both zIIP & zAAP-eligible workloads to process on zIIP.  This capability was ideal for customers with insufficient zAAP or zIIP eligible workload to justify a specialty engine.  Whereas the combined eligible workloads increase the ROI metrics for zIIP deployment.  The zAAP specialty engine is primarily targeted for web-based applications and SOA-based technologies, namely Java and XML.

So for z/OS type workloads, we must “zIIP Into The Future”…

Sometimes we need to look at the big picture, where the IBM organization is comprised of many business units, including the Mainframe business unit.  The Mainframe business unit itself contains many groups, including, but not limited to, the Hardware and Software groups.

As we all know, z/OS software TCO is significant and so this translates into higher revenues for the IBM Mainframe software group; but what about the IBM Mainframe hardware group?  Perhaps the specialty engines, primarily in the form of zIIP will generate revenue stream for this business unit.  Along with the introduction of zBC12 & zEC12 servers, IBM increased the zIIP to General Purpose (CP) engines ratio to 2:1; meaning you can have 2 zIIP specialty engines with the same capacity as an associated CP engine.  Previously the maximum ratio allowed was 1:1 (Specialty:CP).

What workloads are zIIP eligible?  Over time and since 2006 the amount of workload that is zIIP eligible has increased, primarily due to software development and upgrade efforts of IBM and the 3rd party ISV community:

  • DB2 for z/OS exploits the zIIP capability for portions of eligible data serving, pureXML and utility workloads
  • Other 3rd party DBMS solutions, including ADABAS & IDMS offload workload to zIIP
  • Most Systems Management tools (E.g. OMEGAMON, MAINVIEW, RMF, SYSVIEW, et al)
  • z/OS XML System Services for eligible XML validating and non-validating workloads
  • Other z/OS functions including /OS Communications Server, Global Mirror, CIM Server, et al

What are the benefits of deploying a zIIP specialty engine?

  • Lower acquisition and maintenance costs, when compared with general CP
  • zIIP engines run at full rated CP speed
  • Offload work (CPU) from General Purpose (CP) engines
  • No cost for Sub-Capacity eligible IBM software (I.E. WLC)

So, one must draw one’s own conclusions, but seemingly the deployment of zIIP engines is a “no brainer”!

Hmmm, once again, evolution is a good thing and the zIIP engine has an 8 year history and its predecessor zAAP, a 10 year history.  This ~10 year period has allowed for user experiences and IBM function developments to evolve a more stable and rounded offering and as previously stated, a product for the IBM Mainframe Hardware group to focus upon.

From a customer viewpoint, zIIP deployment requires a Capacity Planning evolution, which should be reasonably straightforward.  The big difference is the CP to zIIP offload consideration and some of the lessons learned include:

  • Software costs – Multiple-Processors; CP to zIIP Offload Rate; zIIP utilization
  • Hardware costs – Installed Books (total MSU/MIPS capacity); Additional LPAR(s)
  • Peak CPU utilization – Safeguard that zIIP exploitation reduces peak CPU usage
  • CPU per Transaction – Slight increase in CPU (not necessarily elapsed time) as workload switches from CP to zIIP
  • zIIP utilization – Early experiences indicate ~50% zIIP engine busy is a good number

In conclusion, zIIP deployment has been gradual and evolutionary, but many factors indicate that zIIP is here to stay and it is the future.  Seemingly from an IBM viewpoint, with benefit for the Mainframe Hardware Group in terms of the eradication of the zAAP engine, the increase in CP:zIIP ratio to 2:1 and the associated customer benefits of Sub-Capacity software pricing.  From a customer viewpoint, ignoring these pointers might not be wise, as z/OS software costs are significant and CPU resource requirements keep increasing.  Adding extra zIIP CPU capacity reduces hardware and associated software costs and so this is the “no brainer” observation that can’t be ignored for much longer…