Syncsort Survey Unveils 5 Ways Z Users Are Saving Money

January 9, 2018

Syncsort Inc. recently completed its year-end 2017 State-of-the-Mainframe annual survey of IT professionals. Over In the past year, the organizations surveyed increased their spending for mainframe capacity, new mainframe applications, and mainframe data analytics. The IBM z/OS mainframe remains an important focus in organizations, with the majority of respondents reporting that the mainframe serves as the hub for business-critical applications by providing high-volume transaction and database processing.

More interestingly, Syncsort notes high number of respondents indicated they’ll use the mainframe to run revenue-generating services over the next 12 months, another clear indication that the mainframe remains integral to the business.

However, the survey also reflects concerns over the high cost of the mainframe. In effect, mainframe optimization, cost reduction, and spending remain at the forefront, with many organizations looking to leverage zIIP engines to offload general processor cycles, which maximize resources, delays or avoids hardware upgrades, and lowers monthly software charges.

At the same time some organizations are looking at mainframe optimization to fund strategic projects, such as enhanced mainframe data analytics to support better business decisions for meeting SLAs as well as security and compliance initiatives. All of this may relieve pressure to jump to a lower cost platform (x86) in the hope of reducing spending.

But apparently it is not enough in a number of cases. Despite the focus on optimization, the survey notes, nearly 20% of respondents plan to move off the mainframe completely in 2018. DancingDinosaur, however spent decades writing mainframe-is-dead pieces and this invariably takes longer, costs more, often much more, than expected, and sometimes is never fully achieved. The cost of building a no-fail, scalable, and secure business platform has proven to be extremely difficult.

However costly as the mainframe is, you can get it up running dependably for less than you will end up paying to cobble together bare metal x86 boxes. But if you try, please let me know and I will check back with you next year to publicize your success. One exception might be if you opt for a 100% cloud solution; again, let me know if it works and how much you save; I’ll make you a hero.

In the meantime, here are five ways respondents expect to save money by streamlining operations through mainframe-based optimization:

  1. This year organizations aim to redirect budget dollars to strategic projects such as mainframe data analytics. Optimization will primarily focus on general processor usage by leveraging zIIP engines and using MSU optimization tools. Some organizations will take it a step further, and target some candidate workloads to be moved off of the mainframe (possibly to a hybrid cloud) to ensure sufficient capacity remains for business critical applications.
  1. Big data analytics for operational intelligence, security, and compliance will continue to grow and emerge as a critical effort, and ensuring that IT services are delivered effectively to meet SLAs. Mainframe data sources will be critical in helping to address these challenges.
  1. Integration of mainframe data with modern analytics tools will become pervasive and critically important as organizations look to exploit this abundance of information for enhanced visibility. Integrating mainframe machine data will not only provide enhanced visualization but will enable correlation with data sources from other platforms. Additionally, new analytics technologies, like Splunk, will make mainframe application data more readily available to business analysts who typically aren’t mainframe experts while addressing the diminishing pool of mainframe talent by putting rich, easy tools into the hands of newer staff.
  1. SMF and z/OS log data will play an increased role in addressing security exposures, fulfilling audit requirements, and addressing compliance mandates, a key initiative for IT executives and IT organizations. Here think pervasive encryption on Z. Overall, organizations are looking at leveraging analytics platforms for security and compliance. Along with SMF and other z/OS log data they will look to Splunk, Elastic, and Hadoop.
  1. Data movement across the variety of platforms in distributed enterprises presents important challenges that must be secured, monitored, and performed efficiently. With over half of mainframe organizations still lacking full visibility this must become a priority for organizations.

Over the years, DancingDinosaur writes up every opportunity to lower mainframe costs or optimize operations. Find some of these here, here, and here.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

IBM Q Network Promises to Commercialize Quantum

December 14, 2017

The dash to quantum computing is well underway and IBM is preparing to be one of the leaders. When IBM gets there it will find plenty of company. HPE, Dell/EMC, Microsoft and more are staking out quantum claims. In response IBM is speeding the build-out of its quantum ecosystem, the IBM Q Network, which it announced today.

IBM’s 50 qubit system prototype

Already IBM introduced its third generation of quantum computers in Nov., a prototype 50 qubit system. IBM promises online access to the IBM Q systems by the end of 2017, with a series of planned upgrades during 2018. IBM is focused on making available advanced, scalable universal quantum computing systems to clients to explore practical applications.

Further speeding the process, IBM is building a quantum computing ecosystem of big companies and research institutions. The result, dubbed IBM Q Network, will consist of a worldwide network of individuals and organizations, including scientists, engineers, business leaders, and forward thinking companies, academic institutions, and national research labs enabled by IBM Q. Its mission: advancing quantum computing and launching the first commercial applications.

Two particular goals stand out: Engage industry leaders to combine quantum computing expertise with industry-oriented, problem-specific expertise to accelerate development of early commercial uses. The second: expand and train the ecosystem of users, developers, and application specialists that will be essential to the adoption and scaling of quantum computing.

The key to getting this rolling is the groundwork IBM laid with the IBM Q Experience, which IBM initially introduced in May of 2016 as a 5 cubit system. The Q Experience (free) upgrade followed with a 16-qubit upgrade in May, 2017. The IBM effort to make available a commercial universal quantum computer for business and science applications has increased with each successive rev until today with a prototype 50 cubit system delivered via the IBM Cloud platform.

IBM opened public access to its quantum processors over a year ago  to serve as an enablement tool for scientific research, a resource for university classrooms, and a catalyst for enthusiasm. Since then, participants have run more than 1.7M quantum experiments on the IBM Cloud.

To date IBM was pretty easy going about access to the quantum computers but now that they have a 20 cubit system and 50 cubit system coming the company has become a little more restrictive about who can use them. Participation in the IBM Q Network is the only way to access these advanced systems, which involves a commitment of money, intellectual property, and agreement to share and cooperate, although IBM implied at any early briefing that it could be flexible about what was shared and what could remain an organization’s proprietary IP.

Another reason to participate in the Quantum Experience is QISKit, an open source quantum computing SDK anyone can access. Most DancingDinosaur readers, if they want to participate in IBM’s Q Network will do so as either partners or members. Another option, a Hub, is really targeted for bigger, more ambitious early adopters. Hubs, as IBM puts it, provide access to IBM Q systems, technical support, educational and training resources, community workshops and events, and opportunities for joint work.

The Q Network has already attracted some significant interest for organizations at every level and across a variety of industry segments. These include automotive, financial, electronics, chemical, and materials players from across the globe. Initial participants include JPMorgan Chase, Daimler AG, Samsung, JSR Corporation, Barclays, Hitachi Metals, Honda, Nagase, Keio University, Oak Ridge National Lab, Oxford University, and University of Melbourne.

As noted at the top, other major players are staking out their quantum claims, but none seem as far along or as comprehensive as IBM:

  • Dell/EMC is aiming to solve complex, life-impacting analytic problems like autonomous vehicles, smart cities, and precision medicine.
  • HPE appears to be focusing its initial quantum efforts on encryption.
  • Microsoft, not surprisingly, expects to release a new programming language and computing simulator designed for quantum computing.

As you would expect, IBM also is rolling out IBM Q Consulting to help organizations envision new business value through the application of quantum computing technology and provide customized roadmaps to help enterprises become quantum-ready.

Will quantum computing actually happen? Your guess is as good as anyone’s. I first heard about quantum physics in high school 40-odd years ago. It was baffling but intriguing then. Today it appears more real but still nothing is assured. If you’re willing to burn some time and resources to try it, go right ahead. Please tell DancingDinosaur what you find.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

IBM’s POWER9 Races to AI

December 7, 2017

IBM is betting the future of its Power Systems on artificial intelligence (AI). The company introduced its newly designed POWER9 processor publicly this past Tuesday. The new machine, according to IBM, is capable of shortening the training of deep learning frameworks by nearly 4x, allowing enterprises to build more accurate AI applications, faster.

IBM engineer tests the POWER9

Designed for the post-CPU era, the core POWER9 building block is the IBM Power Systems AC922. The AC922, notes IBM, is the first to embed PCI-Express 4.0, next-generation NVIDIA NVLink, and OpenCAPI—3 interface accelerators—which together can accelerate data movement 9.5x faster than PCIe 3.0 based x86 systems. The AC922 is designed to drive demonstrable performance improvements across popular AI frameworks such as Chainer, TensorFlow and Caffe, as well as accelerated databases such as Kinetica.

More than a CPU under the AC922 cover

Depending on your sense of market timing, POWER9 may be coming at the best or worst time for IBM.  Notes industry observer Timothy Prickett Morgan, The Next Platform: “The server market is booming as 2017 comes to a close, and IBM is looking to try to catch the tailwind and lift its Power Systems business.”

As Morgan puts it, citing IDC 3Q17 server revenue figures, HPE and Dell are jockeying for the lead in the server space, and for the moment, HPE (including its H3C partnership in China) has the lead with $3.32 billion in revenues, compared to Dell’s $3.07 billion, while Dell was the shipment leader, with 503,000 machines sold in Q3 2017 versus HPE’s 501,400 machines shipped. IBM does not rank in the top five shippers but thanks in part to the Z and big Power8 boxes, IBM still holds the number three server revenue generator spot, with $1.09 billion in sales for the third quarter, according to IDC. The z system accounted for $673 million of that, up 63.8 percent year-on year due mainly to the new Z. If you do the math, Morgan continued, the Power Systems line accounted for $420.7 million in the period, down 7.2 percent from Q3 2016. This is not surprising given that customers held back knowing Power9 systems were coming.

To get Power Systems back to where it used to be, Morgan continued, IBM must increase revenues by a factor of three or so. The good news is that, thanks to the popularity of hybrid CPU-GPU systems, which cost around $65,000 per node from IBM, this isn’t impossible. Therefore, it should take fewer machines to rack up the revenue, even if it comes from a relatively modest number of footprints and not a huge number of Power9 processors. More than 90 percent of the compute in these systems is comprised of GPU accelerators, but due to bookkeeping magic, it all accrues to Power Systems when these machines are sold. Plus IBM reportedly will be installing over 10,000 such nodes for the US Department of Energy’s Summit and Sierra supercomputers in the coming two quarters, which should provide a nice bump. And once IBM gets the commercial Power9 systems into the field, sales should pick up again, Morgan expects.

IBM clearly is hoping POWER9 will cut into Intel x86 sales. But that may not happen as anticipated. Intel is bringing out its own advanced x86 Xeon machine, Skylake, rumored to be quite expensive. Don’t expect POWER9 systems to be cheap either. And the field is getting more crowded. Morgan noted various ARM chips –especially ThunderX2 from Cavium and Centriq 2400 from Qualcomm –can boost non-X86 numbers and divert sales from IBM’s Power9 system. Also, AMD’s Epyc X86 processors have a good chance of stealing some market share from Intel’s Skylake. So the Power9 will have to fight for every sale IBM wants and take nothing for granted.

No doubt POWER9 presents a good case and has a strong backer in Google, but even that might not be enough. Still, POWER9 sits at the heart of what is expected to be the most powerful data-intensive supercomputers in the world, the Summit and Sierra supercomputers, expected to knock off the world’s current fastest supercomputers from China.

Said Bart Sano, VP of Google Platforms: “Google is excited about IBM’s progress in the development of the latest POWER technology;” adding “the POWER9 OpenCAPI bus and large memory capabilities allow further opportunities for innovation in Google data centers.”

This really is about deep learning, one of the latest hot buzzwords today. Deep learning emerged as a fast growing machine learning method that extracts information by crunching through millions of processes and data to detect and rank the most important aspects of the data. IBM designed the POWER9 chip to manage free-flowing data, streaming sensors, and algorithms for data-intensive AI and deep learning workloads on Linux.  Are your people ready to take advantage of POWER9?

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

Under the Covers of Z Container Pricing

December 1, 2017

Along with the announcement of the z14, or now just Z, last July IBM also introduced container pricing as an upcoming capability of the machine intended to make it both flexible and price competitive. This is expected to happen by the end of this year.

A peak into the IBM z14

Container pricing implied overall cost savings and also simplified deployment. At the announcement IBM suggested competitive economics too, especially when benchmarked against public clouds and on-premises x86 environments.

By now you should realize that IBM has difficulty talking about price. They have lots of excuses relating to their global footprint and such. Funny, other systems vendors that sell globally don’t seem to have that problem. After two decades of covering IBM and the mainframe as a reporter, analyst, and blogger I’ve finally realized why the reticence: that the company’s pricing is almost always high, over-priced compared to the competition.

If you haven’t realized it yet, the only way IBM will talk price is around a 3-year TCO cost analysis. (Full disclosure: as an analyst, I have developed such TCO analyses and am quite familiar with how to manipulate them.) And even then you will have to swallow a number of assumptions and caveats to get the numbers to work.

For example, there is no doubt that IBM is targeting the x86 (Intel) platform with its LinuxONE lineup and especially its newest machine, the Emperor II. For example, IBM reports it can scale a single MongoDB database to 17TB on the Emperor II while running it at scale with less than 1ms response time. That will save up to 37% compared to x86 on a 3-year TCO analysis. The TCO analysis gets even better when you look at a priced-per-core data serving infrastructures. IBM reports it can consolidate thousands of x86 cores on a single LinuxONE server and reduce costs by up to 40%.

So, let’s see what the Z’s container pricing can do for you. IBM’s container pricing is being introduced to allow new workloads to be added onto z/OS in a way that doesn’t impact an organization’s rolling four-hour average while supporting deployment options that makes the most sense for an organization’s architecture while facilitating competitive pricing at an attractive price point relative to that workload.

For example, one of the initial use cases for container pricing revolves around payments workloads, particularly instant payments. That workload will be charged not to any capacity marker but to the number of payments processed. The payment workload pricing grid promises to be highly competitive with the price–per-payment starting at $0.0021 and dropping to $0.001 with volume. “That’s a very predictable, very aggressive price,” says Ray Jones, vice president, IBM Z Software and Hybrid Cloud. You can do the math and decide how competitive this is for your organization.

Container pricing applies to various deployment options—including co-located workloads in an existing LPAR—that present line-of-sight pricing to a solution. The new pricing promises simplified software pricing for qualified solutions. It even offers the possibility, IBM adds, of different pricing metrics within the same LPAR.

Container pricing, however, requires the use of IBM’s software for payments, Financial Transaction Manager (FTM). FTM counts the number of payments processed, which drives the billing from IBM.

To understand container pricing you must realize IBM is not talking about Docker containers. A container to IBM simply is an address space, or group of address spaces, in support of a particular workload. An organization can have multiple containers in an LPAR, have as many containers as it wants, and change the size of containers as needed. This is where the flexibility comes in.

The fundamental advantage of IBM’s container pricing comes from the co-location of workloads to get improved performance and lower latency. The new pricing eliminates what goes on in containers from consideration in the MLC calculations.

To get container pricing, however, you have to qualify. The company is setting up pricing agents around the world. Present your container plans and an agent will determine if you qualify and at what price. IBM isn’t saying anything about how you should present your container plans to qualify for the best deal. Just be prepared to negotiate as hard as you would with any IBM deal.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

BMC’s 12th Annual Mainframe Survey Shows Z Staying Power

November 17, 2017

ARM processors are invading HPC and supercomputer segments. The Power9 is getting closer and closer to general commercial availability. IBM unveiled not one but two new quantum computers. Meanwhile, the Z continues to roll right along without skipping a beat, according to BMC’s 12th mainframe survey.

There is no doubt that the computing landscape is changing dramatically and will continue to change. Yet mainframe shops appear to be taking it all in stride. As Mark Wilson reported on the recently completed SHARE Europe conference in the UK, citing the keynote delivered by Compuware’s CEO Chris O’Malley: “By design, the post-modern mainframe is the most future ready platform in the world: the most reliable, securable, scalable, and cost efficient. Unsurprisingly, the mainframe remains the dominant, growing, and vital backbone for the worldwide economy. However, outdated processes and tools ensnared in an apathetic culture doggedly resistant to change, prevent far too many enterprises from unleashing its unique technical virtues and business value.”  If you doubt we are entering the post-modern mainframe era just look at the LinuxONE Emperor II or the z14.

Earlier this month BMC released its 12th annual mainframe survey. Titled 5 Myths Busted, you can find the report here.  See these myths right below:

  • Myth 1: Organizations have fully optimized mainframe availability
  • Myth 2: The mainframe is in maintenance mode; no one is modernizing
  • Myth 3: Executives are planning to replace their mainframes
  • Myth 4: Younger IT professionals are pessimistic about mainframe careers
  • Myth 5: People working on the mainframe today are all older

Everyone from prestigious executives like O’Malley to a small army of IBMers to lowly bloggers and analysts like DancingDinosaur have been pounding away at discrediting these myths for years. And this isn’t the first survey to thoroughly discredit mainframe skeptics.

The mainframe is growing: 48% of respondents saw MIPS growth in the last 12 months, over 50% of respondents forecast MIPS growth in the next 12 months, and 71% of large shops (10,000 MIPS or more) experienced MIPS growth in the last year. Better yet, these same shops forecast more growth in the next 12 months.

OK, the top four priorities of respondents remained the same this year. The idea that mainframe shops, however, are fully optimized and just cruising is dead wrong. Survey respondents still have a list of to-do of priorities:

  1. Cost reduction/optimization
  2. Data privacy/compliance
  3. Availability
  4. Application modernization

Maybe my favorite myth is that younger people have given up on the mainframe. BMC found that 53% of respondents are under age 50 and of this group, (age 30-49 with under 10 years of experience) overwhelmingly report a very positive view of the the mainframe future. The majority went so far as to say they see the workload of their mainframe growing and also view the mainframe as having a strong position of growth in the industry overall. This is reinforced by the growth of IBM’s Master of the Mainframe competition, which attracts young people in droves, over 85,000 to date, to work with the so-called obsolete mainframe.

And the mainframe, both the Z and the LinuxONE, is packed with technology that will continue to attract young people: Linux, Docker, Kubernetes, Java, Spark, and support for a wide range of both relational databases like DB2 and NoSQL databases like MongoDB. They use this technology to do mobile, IoT, blockchain, and more. Granted most mainframe shops are not ready yet to run these kinds of workloads. IBM, however, even introduced new container pricing for the new Z to encourage such workloads.

John McKenny, BMC’s VP of Strategy, has noticed growing interest in new workloads. “Yes, they continue to be mainly transactional applications but they are aimed to support new digital workloads too, such as doing business with mobile devices,” he noted.  Mobility and analytics, he added, are used increasingly to improve operations, and just about every mainframe shop has some form of cloud computing, often multiple clouds.

The adoption of Linux on the mainframe a decade ago imediatey put an end to the threat posed by x86. Since then, IBM has become a poster child for open source and a slew of new technologies, from Java to Hadoop to Spark to whatever comes next. Although traditional mainframe data centers have been slow to adopt these new technologies some are starting, and that along with innovative machines like the z14 and LinuxONE Emperor ll are what, ultimately, will keep the mainframe young and competitive.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

IBM Introduces Cloud Private to Hybrid Clouds

November 10, 2017

When you have enough technologies lying around your basement, sometimes you can cobble a few pieces together, mix it with some sexy new stuff and, bingo, you have something that meets a serious need of a number of disparate customers. That’s essentially what IBM did with Cloud Private, which it announced Nov. 1.

IBM staff test Cloud Private automation software

IBM intended Cloud Private to enable companies to create on-premises cloud capabilities similar to public clouds to accelerate app dev. Don’t think it as just old stuff; the new platform is built on the open source Kubernetes-based container architecture and supports both Docker containers and Cloud Foundry. This facilitates integration and portability of workloads, enabling them to evolve to almost any cloud environment, including—especially—the public IBM Cloud.

Also IBM announced container-optimized versions of core enterprise software, including IBM WebSphere Liberty, DB2 and MQ – widely used to run and manage the world’s most business-critical applications and data. This makes it easier to share data and evolve applications as needed across the IBM Cloud, private, public clouds, and other cloud environments with a consistent developer, administrator, and user experience.

Cloud Private amounts to a new software platform, which relies on open source container technology to unlock billions of dollars in core data and applications incorporating legacy software like WebSphere and Db2. The purpose is to extend cloud-native tools across public and private clouds. For z data centers that have tons of valuable, reliable working systems years away from being retired, if ever, Cloud Private may be just what they need.

Almost all enterprise systems vendors are trying to do the same hybrid cloud computing enablement. HPE, Microsoft, Cisco, which is partnering with Google on this, and more. This is a clear indication that the cloud and especially the hybrid cloud is crossing the proverbial chasm. In years past IT managers and C-level executives didn’t want anything to do with the cloud; the IT folks saw it as a threat to their on premises data center and the C-suite was scared witless about security.

Those issues haven’t gone away although the advent of hybrid clouds have mitigated some of the fears among both groups. Similarly, the natural evolution of the cloud and advances in hybrid cloud computing make this more practical.

The private cloud too is growing. According to IBM, while public cloud adoption continues to grow at a rapid pace, organizations, especially in regulated industries of finance and health care, are continuing to leverage private clouds as part of their journey to public cloud environments to quickly launch and update applications. This also is what is driving hybrid clouds. IBM estimates companies will spend more than $50 billion globally starting in 2017 to create and evolve private clouds with growth rates of 15 to 20 percent a year through 2020, according to IBM market projections.

The problem facing IBM and the other enterprise systems vendors scrambling for hybrid clouds is how to transition legacy systems into cloud native systems. The hybrid cloud in effect acts as facilitating middleware. “Innovation and adoption of public cloud services has been constrained by the challenge of transitioning complex enterprise systems and applications into a true cloud-native environment,” said Arvind Krishna, Senior Vice President for IBM Hybrid Cloud and Director of IBM Research. IBM’s response is Cloud Private, which brings rapid application development and modernization to existing IT infrastructure while combining it with the service of a public cloud platform.

Hertz adopted this approach. “Private cloud is a must for many enterprises such as ours working to reduce or eliminate their dependence on internal data centers,” said Tyler Best, Hertz Chief Information Officer.  A strategy consisting of public, private and hybrid cloud is essential for large enterprises to effectively make the transition from legacy systems to cloud.

IBM is serious about cloud as a strategic initiative. Although not as large as Microsoft Azure or Amazon Web Service (AWS) in the public cloud, a recent report by Synergy Research found that IBM is a major provider of private cloud services, making the company the third-largest overall cloud provider.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

IBM 3Q17 Results Break Consecutive Quarters Losing Streak

November 2, 2017

DancingDinosaur generally does not follow the daily gyrations of IBM’s stock, assuming that readers like you are not really active investors in the company’s stock. That is not to say, however, that you don’t have an important, even critical interest in the company’s fortunes.  As users of Z or Power systems, you want to know that IBM has the means to continue to invest in and advance your preferred platform.  And a 20+ consecutive quarters losing streak doesn’t exactly inspire confidence.

What is interesting about IBM’s latest 3Q17 financials, which ends the string of consecutive revenue losses, is the performance of the Z and storage, two things most of us are concerned with.

Blockchain simplifies near real-time clearing and settlement

Here is what Martin Schroeter, IBM Senior Vice President and Chief Financial Officer said to the investment analysts he briefs: In Systems, we had strong growth driven by the third consecutive quarter of growth in storage, and a solid launch of our new z14 mainframe, now just called Z, which was available for the last two weeks of the quarter.

DancingDinosaur has followed the mainframe for several decades at least, and the introduction of a new mainframe always boosts revenue for the next quarter or two. The advantages were apparent on Day 1 when the machine was introduced. As DancingDinosaur wrote: You get this encryption automatically, virtually for free. IBM insists it will deliver the z14 at the same price/performance of the z13 or less. The encryption is built into the cost of silicon out of the box.

A few months later IBM introduced a new LinuxOne mainframe, the Emperor II. The new LinuxOne doesn’t yet offer pervasive encryption but provides Secure Service Containers. As it was described here at that time: Through the Secure Service Container data can be protected against internal threats at the system level even from users with elevated credentials or hackers who obtain a user’s credentials, as well as external threats.

Software developers will benefit by not having to create proprietary dependencies in their code to take advantage of these security capabilities. An application only needs to be put into a Docker container for Secure Service Container deployment. The application can be managed using the Docker and Kubernetes tools that are included to make Secure Service Container environments easy to deploy and use. Again, it will likely take a few quarters for LinuxONE shops and other Linux shops to seek out the Emperor II and Secure Service Containers.

Similarly, in recent weeks, IBM has been bolstering its storage offerings. As Schroeter noted, storage, including Spectrum storage and Flash, have been experiencing a few positive quarters and new products should help to continue that momentum. For example, products like IBM Spectrum Protect Plus promises to make data protection available in as little as one hour.

Or the IBM FlashSystem 900, introduced at the end of October promises to deliver efficient, ultra dense flash with CAPEX and OPEX savings due to 3x more capacity in a 2U enclosure. It also offers to maximize efficiency using inline data compression with no application performance impact as it achieves consistent 95 microsecond response times.

But probably the best 3Q news came from the continuing traction IBM’s strategic imperatives are gaining. Here these imperatives—cloud, security, cognitive computing—continue to make a serious contribution to IBM revenue. Third-quarter cloud revenues increased 20 percent to $4.1 billion.  Cloud revenue over the last 12 months was $15.8 billion, including $8.8 billion delivered as-a-service and $7.0 billion for hardware, software and services to enable IBM clients to implement comprehensive cloud solutions.  The annual exit run rate for as-a-service revenue increased to $9.4 billion from $7.5 billion in the third quarter of 2016.  In the quarter, revenues from analytics increased 5 percent.  Revenues from mobile increased 7 percent and revenues from security increased 51 percent. Added Schroeter: Revenue from our strategic imperatives over the last 12 months was also up 10% to $34.9 billion, and now represents 45% of IBM.

OK, so IBM is no longer a $100 + billion company and hasn’t been for some time. Maybe in a few years if blockchain and the strategic imperatives continue to grow and quantum catches fire it may be back over the $100 billion mark, but not sure how much it matters.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

Illusive Networks’ Mainframe Guard to Deter Cyber Attacks

October 18, 2017

At a time when IBM promised that automatic pervasive encryption on the new Z would spell an end to worries about security an Israeli company stepped forward this week to insist that the z14, or just Z, can’t do the entire job. Pervasive encryption can be undermined by Advanced Persistent Threats (APT), which co-op legit users as they access protected data. Illusive Networks introduced its security tool, Mainframe Guard, earlier this week at Sibos in Toronto.

Mainframe Guard enables admins to action against advanced, targeted cyberattacks by detecting and disrupting movement toward critical business assets early in the attack cycle. Illusive deploys sophisticated and confusing honeypots to distract, misguide, and trap an attacker before he or she can touch the data. In short, the security staff can identify and intervene against advanced, targeted cyberattacks by detecting and disrupting movement toward critical business assets early. With the new Z and pervasive security, of course, that data will already be encrypted and the keys safely stored out of reach.

IBM Breach Cost Estimator

At a time when organizations of all types and in every market segment are under attack from hackers, ransomware, data breaches, and more all data center managers should welcome any data protection tools that work. Yet 96% don’t even bother to encrypt—too costly, too cumbersome, too complicated. As DancingDinosaur noted at the Z launch, the list of excuses is endless. Of the 9 billion records breached since 2013 only 4% were encrypted! And you already know why: encryption is tedious, impacts staff, slows system performance, costs money, and more.

Such attitudes, especially at a mainframe shop, invite serious breaches. While IBM’s latest mainframe automatically encrypts all transaction data, the vast majority of systems expose significant vulnerabilities.

Making the situation even worse; the need to secure against innovations such as mobile applications, cloud-based services, and smart devices presents new challenges. “Organizations are sometimes reluctant to upgrade legacy applications and databases on these enterprise servers, particularly in today’s always-on economy. But unless you address every link in the end-to-end process, you haven’t secured it.” noted Andrew Howard, CTO at Kudelski Security, which cites experience remediating mainframe systems in the wake of cyber breaches.

Even older mainframe shops—pre pervasive encryption—can have effective security. Consider adding Mainframe Guard, which requires you to actively follow the threats and initiate defensive actions.

So how might an attacker today get around the Z’s pervasive encryption? The attack typically starts with lurking and watching as legitimate users gain access to the system. The attacker will then impersonate a legit user. Illusive, however, lures the attacker to locations where the attacker may think he or she has found a trove of intelligence gold.  “Remember, the attacker doesn’t know which machine he has landed on,” said Ofer Israeli, CEO of Illusive Networks. Unless the attacker brings inside information, he is blind inside the network.  From there Illusive leads constantly baits the attacker with deceptive information, which the attacker will have to dodge correctly to avoid giving away the attack.

Leveraging Illusive’s deceptive approach, Mainframe Guard works by detecting malicious movement toward the mainframe and providing a non-intrusive method of protecting the systems, the data they host, and the services they support. The solution is comprised of:

  • A family of deceptions for mainframe environments
  • The ability to display mainframe assets along with other sensitive assets in the Illusive Attacker View portion of the management console, which enables security personnel to see potential attack paths toward the mainframe and track the proximity and progress of attackers toward these assets
  • Purpose-built views of the mainframe environment monitor unexpected connections to mainframe servers
  • An interactive layer added to the Illusive Trap Server mimics mainframe behavior and login screens, tricking attackers into believing they are interacting with an actual mainframe system.

When everything is encrypted and the keys, APIs, and more are safeguarded with the Z’s pervasive encryption on top of Illusive’s deceptions, maybe you can finally begin to relax, at least until the next level of attacks start to emerge.

BTW, DancingDinosaur will be away for 2 weeks. Given IBM’s just released Q3 results. you can hear IBM’s relief even before I’m gone.  Expect some celebrating around the Z; nothing like a new machine to boost revenues. Look for DancingDinosaur the week of Nov. 6.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.

IBM combines Power AI and Data Science Experience

October 13, 2017

The AI bandwagon is getting big fast. Gartner reports Global IT spending in 2018 will increase 4.3% over last year topping $3.7 trillion, driven by business strategies tied to varying degrees of digital transformation and more uses around artificial intelligence. AI actually comes out as Gartner’s #1 tech trend for 2018, with the company saying: The ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.

IBM already has made cognitive computing, one of its myriad terms for AI, a strategic imperative. To underscore the point, on Oct. 10 the company announced integrating two key software tools for AI, PowerAI deep learning with the IBM Data Science Experience.  If you were dithering about how to get involved in AI or cognitive computing, here’s a way to start. The Data Science Experience is available through a per-user licensing model while Power AI is available for free, at least for now.

Rethinking the way work works

With this integration, data scientists will be able to develop AI models with the leading open source deep learning frameworks like TensorFlow or Caffe to unlock analytical insights. The Data Science Experience (DSX) is a collaborative workspace that enables users to develop machine learning models and manage their data and trained models. PowerAI adds topnotch deep learning libraries, algorithms, and capabilities from popular open-source frameworks. The deep-learning frameworks will be able to sort through all types of data – sound, text or visuals – to enhance learning models on DSX.

For example, banks today can leverage deep learning to make more informed predictions about clients who might default on credit or to better detect credit card fraud, or sense clients who are ready to switch bank, which would give the bank a chance to make an offer that might save the account and reduce churn.

In manufacturing, deep learning models can be trained to identify potential failures before they happen by analyzing historical data derived from the functioning of equipment. Through such AI-driven predictive analysis, the manufacturer can reduce downtime and boost productivity. As these learning models continuously evolve and get smarter over time, they become more sophisticated, or smarter, at identifying anomalies and can alert the team on site to take remedial action before a production line unexpectedly stops. It also can advise of specific actions to take.

The Distributed Deep Learning library included with PowerAI from IBM Research reduces deep learning training times from weeks to hours. By integrating such capabilities with DSX brings accelerated deep learning to DSX’s collaborative workspace environment, which further speeds the results.

The growth of deep learning and machine learning is fueled, at least in part, by a rapid rise in computing capability via accelerators like NVIDIA Tesla GPUs. IBM optimized the deep learning frameworks like TensorFlow in PowerAI for IBM Power Systems. For example, the company takes advantage of the industry’s only CPU to GPU implementation of the NVIDIA NVLink high-speed interconnect, which acts as a communications superhighway of sorts, to speed the results.

Frameworks like TensorFlow and Caffe democratize insights through AI. This is expected to result in better client experiences sooner and new business models. And now the PowerAI deep learning enterprise software distribution is integrated into the DSX, a collaborative workspace that helps data scientists to build, manage and deploy AI models from which everyone benefits, both the company and its customers, who enjoy a better customer experience.

The PowerAI libraries and algorithms are optimized for the IBM Power Systems S822LC for High Performance Computing, enabling users ranging from data scientists to business analysts to engage in machine and deep learning through the Data Science Experience collaborative environment. Data scientists are particularly well-positioned to look at deep learning to leverage data as a competitive differentiator and asset.

DSX and PowerAI are packaged as two separate software offerings but integrated and designed to work together.  PowerAI is available only on Power systems while DSX is available on IBM Cloud and on-premises through Power or x86.

As IBM puts it: When it comes to deep learning, faster is better, enabling enterprises of all types to tap into the unlimited potential of AI. If you are a Power shop, grab the free PowerAI deal while its available and then sign up at least a few of your users for DSX and see what you can do.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.


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