Posts Tagged ‘mobile’

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 However, outdated processes and tools ensnared in an apathetic culture doggedly resistant to change, prevent far too many enterprises from unleashing its unique technical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 technologywriter.com and here.

Compuware Brings the Mainframe to AWS

October 6, 2017

IBM talks about the power of the cloud for the mainframe and has turned Bluemix into a cloud development and deployment platform for open systems. Where’s the Z?

Now Compuware has made for the past several years quarterly advances in its mainframe tooling, which are now  available through AWS. Not only have those advances made mainframe management and operations more intuitive and graphical through a string of Topaz releases, but with AWS it is now more accessible from anywhere. DancingDinosaur has been reporting on Compuware’s string of Topaz advances for two years, here, here, and here.

By tapping the power of both the cloud and the mainframe, enterprises can deploy Topaz to their global development workforce in minutes, accelerating the modernization of their mainframe environments. As Compuware noted: mainframe shops now have the choice of deploying Topaz on-premise or on AWS. By leveraging the cloud, they can deploy Topaz more quickly, securely, and scale without capital costs while benefiting from new Topaz features as soon as the company delivers them.

To make Topaz work on AWS Compuware turned to Amazon AppStream 2.0 technology, which provides for global development, test, and ops teams with immediate and secure cloud access to Compuware’s entire innovative mainframe Agile/DevOps solution stack, mainly Topaz. Amazon AppStream 2.0 is a fully managed, secure application streaming service that allows users to stream desktop applications from AWS to any device running a web browser.

Cloud-based deployment of Topaz, Compuware notes, allows for significantly faster implementation, simple administration, a virtual integrated development environment (IDE), adaptive capacity, and immediate developer access to software updates. The last of these is important, since Compuware has been maintaining a quarterly upgrade release schedule, in effect delivering new capabilities every 90 days.

Compuware is in the process of patenting technology to offer an intuitive, streamlined configuration menu that leverages AWS best practices to make it easy for mainframe admins to quickly configure secure connectivity between Topaz on AWS and their mainframe environment. It also enables the same connectivity to their existing cross-platform enterprise DevOps toolchains running on-premise, in the cloud, or both. The upshot: organizations can deploy Topaz across their global development workforce in minutes, accelerating the modernization of their mainframe environments.

Using Topaz on AWS, notes Compuware, mainframe shops can benefit in a variety of ways, specifically:

  • Modify, test and debug COBOL, PL/I, Assembler and other mainframe code via an Eclipse-based virtual IDE
  • Visualize complex and/or undocumented application logic and data relationships
  • Manage source code and promote artifacts through the DevOps lifecycle
  • Perform common tasks such as job submission, review, print and purge
  • Leverage a single data editor to discover, visualize, edit, compare, and protect mainframe files and data

The move to the Eclipse-based IDE presents a giant step for traditional mainframe shops trying to modernize. Eclipse is a leading open source IDE with IBM as a founding member. In addition to Eclipse, Compuware also integrates with other modern tools, including Jenkins, SonarSource, Altassian. Jenkins is an open source automation server written in Java that helps to automate the non-human part of software development process with continuous integration while facilitating technical aspects of continuous delivery. SonarSource enables visibility into mainframe application quality. Atlassian develops products for software developers, project managers, and content management and is best known for Jira, its issue tracking application.

Unlike many mainframe ISVs, Compuware has been actively partnering with various innovative vendors to extend the mainframe’s tool footprint and bring the kind of tools to the mainframe that young developers, especially Millennials, want. Yes, it is possible to access the sexy REST-based Web and mobile tools through IBM’s Bluemix, but for mainframe shops it appears kludgy. By giving its mainframe customers access through AWS to advanced tools, Compuware improves on this. And AWS beats Bluemix in terms of cloud penetration and low cost.

All mainframe ISVs should make their mainframe products accessible through the cloud if they want to keep their mainframe products relevant. IBM has its cloud; of course there is AWS, Microsoft has Azure, and Google rounds out the top four. These and others will keep cloud economics competitive for the foreseeable future. Hope to see you in the cloud.

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 technologywriter.com and here.

 

IBM Promises Easy Fast Data Protection

September 1, 2017

Data protection used to be simple. You simply made a couple of copies of your data and stored them someplace safe. That hasn’t worked for years with most enterprises and certainly won’t work going forward. There are too many systems and data. Now you have to contend with virtual machines, NoSQL databases, cloud storage, and more. In the face of growing compliance mandates and threats like ransomware, and a bevy of data protection threats data protection has gotten much more complicated.

Last week IBM simplified it again by announcing IBM Spectrum Protect Plus. It promises to make data protection available in as little as one hour.

IBM achieves tape breakthrough

Turned out August proved to be a good month for IBM storage. In addition to introducing Spectrum Protect Plus IBM and Sony researchers achieved a record of 201 Gb/in2 (gigabits per square inch) in areal density. That translates into the potential to record up to about 330 terabytes (TB) of uncompressed data on a single tape cartridge. Don’t expect commercially available products with this density soon. But you will want it sooner than you may think as organizations face the need to collect, store, and protect massive amounts of data for a wide range of use cases, from surveillance images to analytics to cognitive to, eventually, quantum computing.

IBM Spectrum Protect Plus delivers data availability using snapshot technology for rapid backup, recovery and data management. Designed to be used by virtual machines (VM) and application administrators, it also provides data clone functionality to support and automate DevOps workflows. Unlike other data availability solutions, IBM Spectrum Protect Plus performs data protection and monitoring based on automated Service Level Agreements to ensure proper backup status and retention compliance, noted IBM.

The company has taken to referring Spectrum Protect Plus as the future of data protection, recovery and data reuse. IBM designed it to be fast, modern, light weight, low cost, easy to use, and simple to deploy while delivering rapid time to value.  As noted at the top, the company claims it can make effective data protection available in an hour without relying on highly trained storage experts. Spectrum Protect Plus, delivers data protection, according to IBM, “anyone can manage,” adding that it installs in less than 15 mins.

You get instant data and virtual machine recovery, which you grab from a snapshot. It is so slick, IBM managers say, that “when someone sends you a ransomware letter you can just laugh at them.” Only, of course, if you have been diligent in making backups. Don’t blame the Protect Plus tool, which is thoroughly automated behind scenes. It was announced last week but won’t be available until the fourth quarter of this year.

Protect Plus also brings a handful of new goodies for different stakeholders, as IBM describes it:

  • CIOs get a single view of the backup and recovery status across the data portfolio and the elimination of silos of data backup and recovery.
  • Senior IT Manager (VM and Application Admins) can rapidly self-serve their data availability without complexity. IBM Spectrum Protect Plus also provides an ability to integrate the VM and application backups into the business rules of the enterprise.
  • Senior Application LOB owners can experience data lifecycle management with near instantaneous recovery, copy management, and global search for fast data access and recovery

Specifically designed for virtual machine (VM) environments to support daily administration the product rapidly deploys without agents. It also features a simple, role-based user interface (UI) with intuitive global search for fast recovery.

Data backup and recovery, always a pain in the neck, has gotten even far more complex. For an enterprise data center facing stringent data protection and compliance obligations and juggling the backup of virtual and physical systems, probably across multiple clouds and multiple data centers the challenges and risks have grown by orders of magnitude. You will need tools like Spectrum Protect Plus, especially the Plus part, which IBM insists is a completely new offering.

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 technologywriter.com and here.

 

 

New Software Pricing for IBM Z

July 27, 2017

One of the often overlooked benefits of the introduction of a new mainframe like the Z is cost savings. Even though the machine may cost more, the cost of the performance and capabilities it delivers typically cost less on a per unit basis. In the case of the new Z, it’s not just a modest drop in price/performance. With the new Z, IBM announced, three new Container Pricing models for IBM Z, providing greatly simplified software pricing that promises flexible deployment with competitive economics vs. public clouds and on-premises x86 environments.

Working on the new IBM Z

Here are the three biggest software pricing changes:

  • Predictable and Transparent Container Pricing—providing organizations greatly simplified software pricing that combines flexible deployment with competitive economics vs. public clouds and on-premises x86 environments. To IBM, a container can be any address space, however large and small. You can have any number of containers. “Container Pricing provides collocated workloads with line-of-sight pricing to a solution,” explained Ray Jones, VP, IBM Z Software and Hybrid Cloud. With container pricing, Jones continued, “the client determines where to deploy using WLM, z/OS and SCRT do the rest.”
  • Application dev and test—highly competitive stand-alone pricing for z/OS based development and test workloads. Organizations can increase their DevTest capacity up to 3 times at no additional MLC cost. This will be based on the organization’s existing DevTest workload size. Or a company can choose the multiplier it wants and set the reference point for both MLC and OTC software.
  • Payment systems pricing are based on the business metric of payments volume a bank processes, not the available capacity. This gives organizations much greater flexibility to innovate affordably in a competitive environment, particularly in the fast-growing Instant Payment segment. To use the new per payment pricing, Jones added, up front licensing of IBM Financial Transaction Manager (FTM) software is required.

The Container Pricing options are designed to give clients the predictability and transparency they require for their business. The pricing models are scalable both within and across logical partitions (LPARs) and deliver greatly enhanced metering, capping and billing capabilities. Container Pricing for IBM Z is planned to be available by year-end 2017 and enabled in z/OS V2.2 and z/OS V2.3

Jones introduced the software discounts by reiterating that this was focused on software container pricing for IBM z and promised that there will be a technology software benefit with z14 as there was with the z13. IBM, he added, will offer a way to migrate to the new pricing, “This is a beginning of a new beginning. Clearly as we go forward we want to expand what’s applicable to container pricing.” His clear implication: IBM is intent on expanding the discounting it started when, several years ago, it introduced discounts for mobile transactions running on the z, which was driving up monthly software cost averages as mobile transaction volume began to skyrocket.

To understand the latest changes you need to appreciate what IBM means by container. This is not just about Docker containers. A container to IBM simply is an address space.  An organization can have multiple containers in a logical partition and have as many containers as it wants and change the size of containers as needed.

The fundamental advantage of IBM’s container pricing is that it enables co-location of workloads to get improved performance and remove latency, thus IBM’s repeated references to line-of-sight pricing. In short, this is about MLC (4hr) pricing. The new pricing eliminates what goes on in container from consideration. The price of container is just that; the price of the container. It won’t impact the 4hr rolling average, resulting in very predictable pricing.

The benefits are straightforward: simplified pricing for qualified solutions and allowance to deploy in the best way. And IBM can price competitively to the customer’s solution; in effect solution-specific pricing. When combined with the new price metric-payments pricing IBM trying to put together a competitive cost/price story. Of course, it is all predicated on the actual prices IBM finally publishes.  Let’s hope they are as competitive as IBM implies.

DancingDinosaur never passes up an opportunity to flog IBM for overpricing its systems and services. From discussions with Jones and other IBM during the pre-launch briefings managers the company may finally understand the need to make the mainframe or z or Z or whatever IBM calls it price-competitive on an operational level today. Low TCO or low cost of IOPS or low cost of QoS is not the same.

This is especially important now. Managers everywhere appear to be waking up to the need transform their mainframe-based businesses, at least in part, by becoming competitive digital businesses. DancingDinosaur never imagined that he would post something referencing the mainframe as a cost-competitive system able to rival x86 systems not just on quality of service but on cost. With the IBM Z the company is talking about competing with an aggressive cost strategy. It’s up to you, paying customers, to force them to deliver.

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 technologywriter.com and here.

 

IBM Resurrects Moore’s Law

June 23, 2017

Guess Moore’s Law ain’t as dead as we were led to believe. On Jun 5 IBM and Research Alliance partners GLOBALFOUNDRIES and Samsung, along with equipment suppliers announced the development of an industry-first process to build silicon nano sheet transistors that will enable 5nm chips. Previously, IBM announced a 7nm process using a silicon germanium (SiGe) alloy.

As DancingDinosaur wrote in early Oct. 2015, the last z System that conformed to the expectations of Moore’s Law was the zEC12, introduced Aug 2012. IBM could boast then it had the fastest commercial processor available.  The subsequent z13 didn’t match it in processor speed.  The z13 chip runs a 22 nm core at 5 GHz, one-half a GHz slower than the zEC12, which ran its 32nm core at 5.5 GHz. IBM compensated for the slower chip speed by adding more processors throughout the system to boost I/O and other functions and optimizing the box every way possible.

5nm silicon nano-sheet transistors delivers 40% performance gain

By 2015, the z13 delivered about a 10 percent performance bump per core thanks to the latest tweaks in the core design, such as better branch prediction and better pipelining. But even at one-half Ghz slower, the z13 was the first system to process 2.5 billion transactions a day.  Even more importantly for enterprise data centers, z13 transactions are persistent, protected, and auditable from end-to-end, adding assurance as mobile transactions grow to an estimated 40 trillion mobile transactions per day by 2025. The z13 also received and continues to receive praise for its industry leading security ratings as well as its scalability and flexibility.

Just recently Hitachi announced a partnership with IBM to develop a version of the z13 to run its own operating system, VOS3. The resulting z13 will run the next generation of Hitachi’s AP series.

But IBM isn’t back in pursuit of Moore’s Law just to deliver faster traditional mainframe workloads. Rather, the company is being driven by its strategic initiatives, mainly cognitive computing. As IBM explained in the announcement: The resulting increase in performance will help accelerate cognitive computing, the Internet of Things (IoT), and other data-intensive applications delivered in the cloud. The power savings could also mean that the batteries in smartphones and other mobile products could last two to three times longer than today’s devices, before needing to be charged.

Scientists working as part of the IBM-led Research Alliance at the SUNY Polytechnic Institute Colleges of Nanoscale Science and Engineering’s NanoTech Complex in Albany, NY achieved the breakthrough by using stacks of silicon nanosheets as the device structure of the transistor instead of the standard FinFET architecture, which is the blueprint for the semiconductor industry up through 7nm node technology. “For business and society to meet the demands of cognitive and cloud computing in the coming years, advancement in semiconductor technology is essential,” said Arvind Krishna, senior vice president, Hybrid Cloud, and director, IBM Research in the announcement. “That’s why IBM aggressively pursues new and different architectures and materials that push the limits of this industry, and brings them to market in technologies like mainframes and our cognitive systems.”

Compared to the leading edge 10nm technology available in the market, according to IBM, a nanosheet-based 5nm technology can deliver 40 percent performance enhancement at fixed power, or 75 percent power savings at matched performance. This improvement enables a significant boost to meeting the future demands of artificial intelligence (AI) systems, virtual reality, and mobile devices.

These may not sound like the workloads you are running on your mainframe now, but systems with these chips are not going to be shipped in the next mainframe either. So, you have a couple of years. The IBM team expects to make progress toward commercializing 7nm in 2018. By the time they start shipping 5nm systems you might be desperate for a machine to run such workloads and others like them.

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 technologywriter.com and here.

 

IBM On-Premises Cognitive Means z Systems Only

February 16, 2017

Just in case you missed the incessant drumbeat coming out of IBM, the company committed to cognitive computing. But that works for z data centers since IBM’s cognitive system is available on-premises only for the z. Another z first: IBM just introduced Machine Learning (key for cognitive) for the private cloud starting with the z.

ibm-congitive-graphic

There are three ways to get IBM cognitive computing solutions: the IBM Cloud, Watson, or the z System, notes Donna Dillenberger, IBM Fellow, IBM Enterprise Solutions. The z, however, is the only platform that IBM supports for cognitive computing on premises (sorry, no Power). As such, the z represents the apex of programmatic computing, at least as IBM sees it. It also is the only IBM platform that supports cognitive natively; mainly in the form of Hadoop and Spark, both of which are programmatic tools.

What if your z told you that a given strategy had a 92% of success. It couldn’t do that until now with IBM’s recently released cognitive system for z.

Your z system today represents the peak of programmatic computing. That’s what everyone working in computers grew up with, going all the way back to Assembler, COBOL, and FORTRAN. Newer languages and operating systems have arrived since; today your mainframe can respond to Java or Linux and now Python and Anaconda. Still, all are based on the programmatic computing model.

IBM believes the future lies in cognitive computing. Cognitive has become the company’s latest strategic imperative, apparently trumping its previous strategic imperatives: cloud, analytics, big data, and mobile. Maybe only security, which quietly slipped in as a strategic imperative sometime 2016, can rival cognitive, at least for now.

Similarly, IBM describes itself as a cognitive solutions and cloud platform company. IBM’s infatuation with cognitive starts with data. Only cognitive computing will enable organizations to understand the flood of myriad data pouring in—consisting of structured, local data but going beyond to unlock the world of global unstructured data; and then to decision tree-driven, deterministic applications, and eventually, probabilistic systems that co-evolve with their users by learning along with them.

You need cognitive computing. It is the only way, as IBM puts it: to move beyond the constraints of programmatic computing. In the process, cognitive can take you past keyword-based search that provides a list of locations where an answer might be located to an intuitive, conversational means to discover a set of confidence-ranked possibilities.

Dillenberger suggests it won’t be difficult to get to the IBM cognitive system on z . You don’t even program a cognitive system. At most, you train it, and even then the cognitive system will do the heavy lifting by finding the most appropriate training models. If you don’t have preexisting training models, “just use what the cognitive system thinks is best,” she adds. Then the cognitive system will see what happens and learn from it, tweaking the models as necessary based on the results and new data it encounters. This also is where machine learning comes in.

IBM has yet to document payback and ROI data. Dillenberger, however, has spoken with early adopters.  The big promised payback, of course, will come from the new insights uncovered and the payback will be as astronomical or meager as you are in executing on those insights.

But there also is the promise of a quick technical payback for z data centers managers. When the data resides on z—a huge advantage for the z—you just run analytics where the data is. In such cases you can realize up to 3x the performance, Dillenberger noted.  Even if you have to pull data from some other location too you still run faster, maybe 2x faster. Other z advantages include large amounts of memory, multiple levels of cache, and multiple I/O processors get at data without impacting CPU performance.

When the data and IBM’s cognitive system resides on the z you can save significant money. “ETL consumed huge amounts of MIPS. But when the client did it all on the z, it completely avoided the costly ETL process,” Dillenberger noted. As a result, that client reported savings of $7-8 million dollars a year by completely bypassing the x-86 layer and ETL and running Spark natively on the z.

As Dillenberger describes it, cognitive computing on the z is here now, able to deliver a payback fast, and an even bigger payback going forward as you execute on the insights it reveals. And you already have a z, the only on-premises way to IBM’s Cognitive System.

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 technologywriter.com and here.

 

Arcati 2017 Mainframe Survey—Cognitive a No-Show

February 2, 2017

DancingDinosaur checks into Arcati’s annual mainframe survey every few years. You can access a copy of the 2017 report here.  Some of the data doesn’t change much, a few percentage points here or there. For example, 75% of the respondents consider the mainframe too expensive. OK, people have been saying that for years.

On the other hand, 65% of the respondents’ mainframes are involved with web services. Half also run Java-based mainframe apps, up from 30% last year, while 17% more are planning to run Java with their mainframe this year. Similarly, 35% of respondents report running Linux on the mainframe, up from 22% last year. Again, 13% of the respondents expect to add Linux this year.  Driving this is the advantageous cost and management benefits that result from consolidating distributed Linux workloads on the z. Yes, things are changing.

linuxone-5558_d_ibm_linuxone_social_tile_990_550_4_081515

The biggest surprise for DancingDinosaur, however, revolved around IBM’s latest strategic initiatives, especially cognitive computing and blockchain.  Other strategic initiatives may include, depending on who is briefing you at the moment—security, data analytics, cloud, hybrid cloud, and mobile. These strategic imperatives, especially cognitive computing, are expected to drive IBM’s revenue. In the latest statement, reported last week in DancingDinosaur, strategic imperatives amounted to 41% of revenue.  Cloud revenue and Cloud-as-a-service also rose considerably, 35% and 61% respectively.

When DancingDinosaur searched the accompanying Arcati vendor report (over 120 vendors with brief descriptions) for cognitive only GT Software came up. IBM didn’t even mention cognitive in its vendor listing, which admittedly was skimpy. The case was the same with Blockchain; only one vendor, Atos, mentioned it and nothing about blockchain in the IBM listing. More vendors, however, noted supporting one or some of the other supposed strategic initiatives.

Overall, the Arcati survey is quite positive about the mainframe. The survey found that 50 percent of sites viewed their mainframe as a legacy system (down from last year’s 62 percent). However, 22 percent (up from 16 percent last year) viewed mainframe as strategic, with 28 percent (up from 22 percent) viewing mainframes as both strategic and legacy.

Reinforcing the value of the mainframe, the survey found 78 percent of sites experienced some kind of increase in capacity. With increased demand for mainframe resources (data and processing), it should not be surprising that respondents report an 81 percent an increase in technology costs. Yet, 38 percent of sites report their people costs have decreased or stayed the same.

Unfortunately, the survey also found that 70 percent of respondents thought there were a cultural barrier between mainframe and other IT professionals. That did not discourage respondents from pointing out the mainframe advantages: 100 percent highlighted the benefit of the mainframe’s availability, 83 percent highlighted security, 75 percent identified scalability, and 71 percent picked manageability as a mainframe benefit.

Also, social media runs on the mainframe. Respondents found social media (Facebook, Twitter, YouTube) useful for their work on the mainframe. Twenty-seven percent report using social (up slightly from 25 percent last year) with the rest not using it at all despite IBM offering Facebook pages dedicated to IMS, CICS, and DB2. DancingDinosaur, only an occasional FB visitor, will check it out and report.

In terms of how mainframes are being used, the Arcati survey found that 25 percent of sites are planning to use Big Data; five percent of sites have adopted it for DevOps while 48 percent are planning to use mainframe DevOps going forward. Similarly, 14 percent of respondents already are reusing APIs while another 41 percent are planning to.

Arcati points out another interesting thought: The survey showed a 55:45 percent split in favor of distributed systems. So, you might expect the spend on the two types of platform to be similar. Yet, the survey found that 87 percent of an organization’s IT spend was going to distributed systems! Apparently mainframes aren’t as expensive as people think. Or put it another way, the cost of owning and operating distributed systems with mainframe-caliber QoS amounts to a lot more than people are admitting.

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 technologywriter.com and here.

 

IBM Cheers Beating Estimates But Losing Streak Continues

January 26, 2017

It has been 19 quarters since IBM reported positive revenue in its quarterly reports but the noises coming out of IBM with the latest 4Q16 and full year 2016 financials are upbeat due to the company beating analyst consensus revenue estimates and its strategic initiatives are starting to generate serious revenue.   Although systems revenues were down again (12%) the accountants at least had something positive to say about the z: “gross profit margins improved driven by z Systems performance.”

ezsource-dashboard

EZSource: Dashboard visualizes changes to mainframe code

IBM doesn’t detail which z models were contributing but you can guess they would be the LinuxONE models (Emperor and Rock Hopper) and the z13. DancingDinosaur expects z performance to improve significantly in 2017 when a new z, which had been heavily hinted in the 3Q2016 results reported here, is expected to ship.

With it latest financials IBM is outright crowing about its strategic initiatives: Fourth-quarter cloud revenues increased 33 percent.  The annual exit run rate for cloud as-a-service revenue increased to $8.6 billion from $5.3 billion at year-end 2015.  Revenues from analytics increased 9 percent.  Revenues from mobile increased 16 percent and revenues from security increased 7 percent.

For the full year, revenues from strategic imperatives increased 13 percent.  Cloud revenues increased 35 percent to $13.7 billion.  The annual exit run rate for cloud as-a-service revenue increased 61 percent year to year.  Revenues from analytics increased 9 percent.  Revenues from mobile increased 34 percent and from security increased 13 percent.

Of course, cognitive computing is IBM’s strategic imperative darling for the moment, followed by blockchain. Cognitive, for which IBM appears to use an expansive definition, is primarily a cloud play as far as IBM is concerned.  There is, however, a specific role for the z, which DancingDinosaur will get into in a later post. Blockchain, on the other hand, should be a natural z play.  It is, essentially, extremely secure OLTP on steroids.  As blockchain scales up it is a natural to drive z workloads.

As far as IBM’s financials go the strategic imperatives indeed are doing well. Other business units, however, continue to struggle.  For instance:

  • Global Business Services (includes consulting, global process services and application management) — revenues of $4.1 billion, down 4.1 percent.
  • Systems (includes systems hardware and operating systems software), remember, this is where z and Power platforms reside — revenues of $2.5 billion, down 12.5 percent. But as noted above, gross profit margins improved, driven by z Systems performance.
  • Global Financing (includes financing and used equipment sales) — revenues of $447 million, down 1.5 percent.

A couple of decades ago, when this blogger first started covering IBM and the mainframe as a freelancer writing for any technology publication that would pay real money IBM was struggling (if $100 billion behemoths can be thought to be struggling). The buzz among the financial analysts who followed the company was that IBM should be broken up into its parts and sold off.  IBM didn’t take that advice, at least not exactly, but it did begin a rebound that included laying off tons of people and the sale of some assets. Since then it invested heavily in things like Linux on z and open systems.

In December IBM SVP Tom Rosamilia talked about new investments in z/OS and z software like DB2 and CICS and IMS, and the best your blogger can tell he is still there. (Rumors suggest Rosamilia is angling for Rometty’s job in two years.)  If the new z does actually arrive in 2017 and key z software is refreshed then z shops can rest easy, at least for another few quarters.  But whatever happens, you can follow it 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 technologywriter.com and here.

 

z System-Power-Storage Still Live at IBM

January 5, 2017

A mid-December briefing by Tom Rosamilia, SVP, IBM Systems, reassured some that IBM wasn’t putting its systems and platforms on the backburner after racking up financial quarterly losses for years. Expect new IBM systems in 2017. A few days later IBM announced that Japan-based APLUS Co., Ltd., which operates credit card and settlement service businesses, selected IBM LinuxONE as its mission-critical system for credit card payment processing. Hooray!

linuxone-emperor-2

LinuxONE’s security and industry-leading performance will ensure APLUS achieves its operational objectives as online commerce heats up and companies rely on cloud applications to draw and retain customers. Especially in Japan, where online and mobile shopping has become increasingly popular, the use of credit cards has grown, with more than 66 percent of consumers choosing that method for conducting online transactions. And with 80 percent enterprise hybrid cloud adoption predicted by 2017, APLUS is well positioned to connect cloud transactions leveraging LinuxONE. Throw in IBM’s expansion of blockchain capabilities and the APLUS move looks even smarter.

With the growth of international visitors spending money, IBM notes, and the emergence of FinTech firms in Japan have led to a diversification of payment methods the local financial industry struggles to respond. APLUS, which issues well-known credit cards such as T Card Plus, plans to offer leading-edge financial services by merging groups to achieve lean operations and improved productivity and efficiency. Choosing to update its credit card payment system with LinuxONE infrastructure, APLUS will benefit from an advanced IT environment to support its business growth by helping provide near-constant uptime. In addition to updating its server architecture, APLUS has deployed IBM storage to manage mission-critical data, the IBM DS8880 mainframe-attached storage that delivers integration with IBM z Systems and LinuxONE environments.

LinuxONE, however, was one part of the IBM Systems story Rosamilia set out to tell.  There also is the z13s, for encrypted hybrid clouds and the z/OS platform for Apache Spark data analytics and even more secure cloud services via blockchain on LinuxONE, by way of Bluemix or on premises.

z/OS will get attention in 2017 too. “z/OS is the best damn OLTP system in the world,” declared Rosamilia. He went on to imply that enhancements and upgrades to key z systems were coming in 2017, especially CICS, IMS, and a new release of DB2. Watch for new announcements coming soon as IBM tries to push z platform performance and capacity for z/OS and OLTP.

Rosamilia also talked up the POWER story. Specifically, Google and Rackspace have been developing OpenPOWER systems for the Open Compute Project.  New POWER LC servers running POWER8 and the NVIDIA NVLink accelerator, more innovations through the OpenCAPI Consortium, and the team of IBM and Nvidia to deliver PowerAI, part of IBM’s cognitive efforts.

As much as Rosamilia may have wanted to talk about platforms and systems IBM continues to avoid using terms like systems and platforms. So Rosamilia’s real intent was to discuss z and Power in conjunction with IBM’s strategic initiatives.  Remember these: cloud, big data, mobile, analytics. Lately, it seems, those initiatives have been culled down to cloud, hybrid cloud, and cognitive systems.

IBM’s current message is that IT innovation no longer comes from just the processor. Instead, it comes through scaling performance by workload and sustaining leadership through ecosystem partnerships.  We’ve already seen some of the fruits of that innovation through the Power community. Would be nice to see some of that coming to the z too, maybe through the open mainframe project. But that isn’t about z/0S. Any boost in CICS, DB2, and IMS will have to come from the core z team. The open mainframe project is about Linux on z.

The first glimpse we had of this came last spring in a system dubbed Minsky, which was described back then by commentator Timothy Prickett Morgan. With the Minsky machine, IBM is using NVLink ports on the updated Power8 CPU, which was shown in April at the OpenPower Summit and is making its debut in systems actually manufactured by ODM Wistron and rebadged, sold, and supported by IBM. The NVLink ports are bundled up in a quad to deliver 80 GB/sec bandwidth between a pair of GPUs and between each GPU and the updated Power8 CPU.

The IBM version, Morgan describes, aims to create a very brawny node with very tight coupling of GPUs and CPUs so they can better share memory, have fewer overall GPUs, and more bandwidth between the compute elements. IBM is aiming Minsky at HPC workloads, according to Morgan, but there is no reason it cannot be used for deep learning or even accelerated databases.

Is this where today’s z data center managers want to go?  No one is likely to spurn more performance, especially if it is accompanied with a price/performance improvement.  Whether rank-and-file z data centers are queueing up for AI or cognitive workloads will have to be seen. The sheer volume and scale of expected activity, however, will require some form of automated intelligent assist.

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 technologywriter.com and here

IBM Power System S822LC for HPC Beat Sort Record by 3.3x

November 17, 2016

The new IBM Power System S822LC for High Performance Computing servers set a new benchmark for sorting by taking less than 99 seconds (98.8 seconds) to finish sorting 100 terabytes of data in the Indy GraySort category, improving on last year’s best result, 329 seconds, by a factor of 3.3. The win proved a victory not only for the S822LC but for the entire OpenPOWER community. The team of Tencent, IBM, and Mellanox has been named the Winner of the Sort Benchmark annual global computing competition for 2016.

rack-of-new-ibm-power-systems-s822lc-for-high-performance-computing-servers-1Power System S822LC for HPC

Specifically, the machine, an IBM Power S822LC for High Performance Computing (HPC), features NVIDIA NVLink technology optimized for the Power architecture and NVIDIA’s latest GPU technology. The new system supports emerging computing methods of artificial intelligence, particularly deep learning. The combination, newly dubbed IBM PowerAI, provides a continued path for Watson, IBM’s cognitive solutions platform, to extend its artificial intelligence expertise in the enterprise by using several deep learning methods to train Watson.

Actually Tencent Cloud Data Intelligence (the distributed computing platform of Tencent Cloud) won each category in both the GraySort and MinuteSort benchmarks, establishing four new world records with its performance, outperforming the 2015 best speeds by 2-5x. Said Zeus Jiang, Vice President of Tencent Cloud and General Manager of Tencent’s Data Platform Department: “In the future, the ability to manage big data will be the foundation of successful Internet businesses.”

To get this level of performance Tencent runs 512 IBM OpenPOWER LC servers and Mellanox’100Gb interconnect technology, improving the performance of Tencent Cloud big data products with the infrastructure. Online prices for the S822LC starts at about $9600 for 2-socket, 2U with up to 20 cores (2.9-3.3Ghz), 1 TB memory (32 DIMMs), 230 GB/sec sustained memory bandwidth, 2x SFF (HDD/SSD), 2 TB storage, 5 PCIe slots, 4 CAPI enabled, up to 2 NVidia K80 GPU. Be sure to shop for volume discounts.

The 2016 Sort Benchmark Results below (apologies in advance if this table breaks apart)

Sort Benchmark Competition 20 Records (Tencent Cloud ) 2015 World Records 2016 Improvement
Daytona GraySort 44.8 TB/min 15.9 TB/min 2.8X greater performance
Indy GraySort 60.7 TB/min 18.2 TB/min 3.3X greater performance
Daytona MinuteSort 37 TB/min 7.7 TB/min 4.8X greater performance
Indy MinuteSort 55 TB/min 11 TB/min 5X greater performance

Pretty impressive, huh. As IBM explains it: Tencent Cloud used 512 IBM OpenPOWER servers and Mellanox’100Gb interconnect technology, improving the performance of Tencent Cloud big data products with the infrastructure. Then Tom Rosamilia, IBM Senior VP weighed in: “Industry leaders like Tencent are helping IBM and our OpenPOWER partners push performance boundaries for a cognitive era defined by big data and advanced analytics.” The computing record achieved by Tencent Cloud on OpenPOWER turned out to be an important milestone for the OpenPOWER Foundation too.

Added Amir Prescher, Sr. Vice President, Business Development, at Mellanox Technologies: “Real-time-analytics and big data environments are extremely demanding, and the network is critical in linking together the extra high performance of IBM POWER-based servers and Tencent Cloud’s massive amounts of data,” In effect, Tencent Cloud developed an optimized hardware/software platform to achieve new computing records while demonstrating that Mellanox’s 100Gb/s Ethernet technology can deliver total infrastructure efficiency and improve application performance, which should make it a favorite for big data applications.

Behind all of this was the new IBM Power System S822LC for High Performance Computing servers. Currently the servers feature a new IBM POWER8 chip designed for demanding workloads including artificial intelligence, deep learning and advanced analytics.  However, a new POWER9 chips has already been previewed and is expected next year.  Whatever the S822LC can do running POWER8 just imagine how much more it will do running POWER9, which IBM describes as a premier acceleration platform. DancingDinosaur covered POWER9 in early Sept. here.

To capitalize on the hardware, IBM is making a new deep learning software toolkit available, PowerAI, which runs on the recently announced IBM Power S822LC server built for artificial intelligence that features NVIDIA NVLink interconnect technology optimized for IBM’s Power architecture. The hardware-software combination provides more than 2X performance over comparable servers with 4 GPUs running AlexNet with Caffe. The same 4-GPU Power-based configuration running AlexNet with BVLC Caffe can also outperform 8 M40 GPU-based x86 configurations, making it the world’s fastest commercially available enterprise systems platform on two versions of a key deep learning framework.

Deep learning is a fast growing, machine learning method that extracts information by crunching through millions of pieces of data to detect and ranks the most important aspects of the data. Publicly supported among leading consumer web and mobile application companies, deep learning is quickly being adopted by more traditional enterprises across a wide range of industry sectors; in banking to advance fraud detection through facial recognition; in automotive for self-driving automobiles; and in retail for fully automated call centers with computers that can better understand speech and answer questions. Is your data center ready for deep learning?

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 technologywriter.com and here.

 

 


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