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Monday, September 25, 2017

IBM Research on the road to commercial Quantum Computing

By Rich Ptak


Dario Gil, Vice President AI, IBM Research and Bob Sutor, Vice President AI, Blockchain, and Quantum Solutions, IBM Research recently provided a briefing IBM’s perspective on the state of Quantum Computing. They describe three phases in the evolution of Quantum Computing. They describe IBM efforts and contributions as well as a very recent and significant IBM Research breakthrough on the road to commercializing quantum computing.

The breakthrough is in practical Quantum Computing technology. It marks a significant advance towards commercialization of Quantum Computing. We’ll talk about why in a minute. First a few words about quantum computing. The building blocks of this technology are quantum bits, or qubits, which are the quantum informational equivalent of classical bits, the basis of contemporary computing. Bits have only two states. They are either 0 or 1, i.e. binary – from there all of computing is built.

Individual qubits can exist in much more complex states than simple 0’s and 1’s, storing information in phases and amplitudes. Additionally, the states of multiple qubits can be entangled, meaning that their states are no longer independent of each other. The fact that quantum information can be represented and manipulated in these ways allows us to approach algorithms (instructions that are used to solve problems) fundamentally differently, opening up opportunities for exponentially faster computation. A major challenge to be overcome is how to design algorithms that can make use of these properties to solve problems that are traditionally difficult for conventional machines, like efficiently simulating materials. In this case the molecules at the heart of chemistry and material science.

A cover story article in the September issue of Nature magazine details how IBM researchers demonstrated a highly efficient algorithm that simulates beryllium hydride (BeH2), and then implemented that algorithm on a real quantum computer. This demonstration was the largest molecular simulation on a quantum computer to date. You can link to the article here. Unfortunately, it is behind a paywall, but there are plenty of other highly interesting articles on Quantum technology and other topics available there. IBM’s announcement with a short explanation can be found here. Read the article for more details about the breakthrough.

What matters today to enterprises, business and more

The most enterprise-significant parts of the announcement are in the implication for commercial enterprises. These are exposed in the details of IBM’s vision and focus about the commercialization of Quantum Computing technology. It provides insightful information and structure for making decisions about when to begin investigating Quantum Computing and its potential to affect your enterprise or business.
Image Courtesy of IBM, Inc. 

IBM considers the initial commercialization of Quantum Computing to be within sight. It may be as much as a decade away, but can reasonably be considered to be close enough for some early enterprise movers with interest, resources, and vision to begin exploring the technology and its potential.

Let’s position where Quantum Computing is today. The speakers described three phases of Quantum Computing These are:
·        Phase 1 – development of Quantum Science – interest began in the 1920’s, it wasn’t until the 1970’s that the attention of computer scientists’ attention was captured. This led to a decades-long effort to discover and define the physics of quantum technology and then develop the theories and concepts to build-out the science leading to Quantum Computing technology. Quantum Science underlies the entire field, and will continue as long as there is research to be done to continue to advance the technology.
·         Phase 2 – emergence of Quantum Technology – began May 2016 when IBM provided free access to the first publicly-accessible Quantum Computing prototype, e.g. IBM Q experience, on the IBM Cloud. The opportunity to experiment on a real device led to the creation of new problem-solving tools, algorithms, and even games as real Quantum Computers became accessible to the first wave of users beyond theoretical physicists and computer theoreticians. These new users are practitioners; developers, engineers, thinkers and researchers including scientists, chemists, mathematicians, etc. Their efforts focus on understanding and articulating problems in quantum terms. The phase will end when the now-wider quantum information community discovers the first applications where the use of quantum computing offers an advantage for solving certain classes of problems. This leads to the next phase…
·         Phase 3 – the age of Quantum Advantage – the age of full commercialization of Quantum Computing. It will be marked with the delivery of apps able to fully exploit Quantum Technology to solve commercial problems. Quantum Computing begins to compete, in some areas, with traditional computing methods by offering multiple orders of magnitude increases in processing speeds and computational complexity for certain classes of problems.

Things to keep in mind and conclusions:

Quantum Computing systems that can handle commercial-scale problems don’t exist yet. A considerable amount of research and development work needs to be done before you can begin to contemplate configuring a system of software and infrastructure. But the first serious prototype systems that lay the foundations for the more mature machines of the future do exist. Is it time to begin to develop some understanding of Quantum Computing, how it functions and how it is currently being used?
Quantum Computing will complement, not replace, traditional computing. By its nature, it is best suited to solving certain classes of problems that are traditionally-difficult to solve with conventional machines. These are problems where solving them requires evaluating many alternatives to find the best solution, each of which alternatives may be computationally intensive to evaluate. Today, many problems are addressed (and will remain so) with traditional computing simulation, modeling and statistical analysis, albeit while making simplifying assumptions. For many applications, solutions obtained with traditional computing techniques will be adequate. Also, despite some recent claims, Quantum Computing does not invalidate or decrease the need for recently announced advances in computing security. Such protections will remain critical to secure computing long into the future. 
For other applications, computing alternatives are needed, especially in cases that require simulating quantum behaviors. These include modeling chemical compounds, which requires the ability to predict molecular-level interactions. It is believed that wherever the analysis involves evaluating an incredibly large number of combinations of items, Quantum Computing will have a distinct advantage. Some other examples of nearer-term applications of Quantum Computing include optimization and machine learning.
So, what’s the conclusion? First, as we said, commercialized Quantum Computing is still in the future. It is not ready to address short- or medium-term issues. But, that day is coming. At this stage, most can ignore this technology. But, there also are some that should allocate a portion of their resources (time, budget) to get educated about Quantum Computing. Quantum Computing will realize its biggest advantages when users can define problems in its terms. That requires an understanding of the technology.
Clearly, the level of recommended activity varies with the potential to impact. You need to get a realistic idea of that potential. One approach would be to take advantage of IBM’s offer for free access to its Quantum Computing prototype[1]. Another approach would be to fund a sandbox project, or an off-hours task to learn more about and explore quantum technology.  AND thinking about problems in Quantum terms. IBM is making a considerable amount of resources available to do so, much of which is free, some not.  
In summary, our advice is to concentrate on:
·         Understanding the basics of Quantum Computing approach to determine its potential to impact you and your business. We expect most will find its potential optimization benefits too attractive to resist.
·         Learning about and understanding how Quantum Computing will change how problems are viewed, articulated and programmed for solutions.
·         Considering encouragement of “sandbox” or “off-hours” efforts to learn more about Quantum Computing; formal or informal depending on organizational resources and culture.
·         If the potential impact is significant (and we think it is for many), assign a senior executive the responsibility to keep current on the status of Quantum Computing. 
Finally, there exists no single standard for comparing Quantum Computing status today. The metric of the number of qubits available in an array (that makes up a system) – is insufficient.  For a time, conventional “wisdom” posited it as ‘horse-race’ with more qubits being better.
However, the number of qubits alone don’t work if there isn’t time to execute an algorithm (application) before a qubit array ‘ages’ to a bit and loses the data. A way needs to be found to control/correct such error rates. There are three issues: 1) the life of the qubit array, 2) the time for an algorithm to execute, 3) error correction/avoidance.
Researchers are working on these but no single metric yet exists to measure and relate progress. More about these efforts and other issues appear in IEEE Spectrum and Nature magazine, mentioned earlier. 




Publication Date: September 25, 2017
This document is subject to copyright.  No part of this publication may be reproduced by any method whatsoever without the prior written consent of Ptak Associates LLC. 

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All trademarks are the property of their respective owners.

While every care has been taken during the preparation of this document to ensure accurate information, the publishers cannot accept responsibility for any errors or omissions.  Hyperlinks included in this paper were available at publication time. 

About Ptak Associates LLC
We cover a breadth of areas to bring you a complete picture of technology trends across the industry. Whether it's Cloud, Mobile, Analytics, Big Data, DevOps, IoT, Cognitive Computing or other emerging trend, we cover these trends with a uniquely deep and broad perspective.

Our clients include industry leaders and dynamic newcomers. We help IT organizations understand and prioritize their needs within the context of present and near-future IT trends, enabling them to apply IT technology to enterprise challenges. We help technology vendors refine strategies, and provide them with both market insight and deliverables that communicate the enterprise values of their services. We support clients with our understanding how their competitors play in their market space, and deliver actionable recommendations.




Friday, August 11, 2017

IBM + Partners breathe new life into Moore’s Law with 5NM chip technology

By Rich Ptak and Bill Moran


When IBM exited the chip foundry business several years ago most industry watchers were sad to see the company go. A key player for decades in semiconductor research, IBM would definitely be missed. We thought that the industry had suffered a real loss. We and others thought statements of IBM’s commitment to making further investments in semiconductor research were to be written off as an essentially meaningless face saving gestures.

As it turns out, we couldn’t have been more wrong. In fact, IBM research continued the work on semiconductor research that it had been doing for nearly 50[1] years.  The IBM-organized consortium of IBM, Global Foundries, and Samsung based at NY State’s SUNY campus in Albany, is delivering a significant breakthrough in semiconductor technology research.  Exiting the chip foundry business was not a sufficient reason for IBM Research to cease its efforts.

Here’s some background on what IBM and its partners have accomplished. Moore’s law[2] says that the number of transistors on a chip will double approximately every two years. The results of that law drove the semiconductor industry for decades.
A meter being roughly a yard.  It might have been more fun if the industry has used the term “nanoyard”. However, as the topic is worldwide technology, the metric system is used, as is the practice in global technical and scientific circles.
Recently, much published commentary (ours and others) discussed how the law was reaching the end of its useful life. A major reason being the physical limits of chip geometry. Incidentally, one of the effects of law is that today’s cellphones (which fit in a pocket) have more processing power than the 1960’s computers used for the Moon visit (which occupied an entire very large room).

To understand what is going on, we need a little computer industry technology background. The industry initially measured processing speeds in seconds. Things moved faster so the term “milliseconds” (one-thousandth of a second) became standard. As the speed-up continued, the “microsecond” (one-millionth of a second) became the standard. One might imagine that things could not get much faster, wrong. Today’s process speeds are measured in “nanoseconds”, i.e. billionths of a second.   

Moving to semiconductors, chip size is measured in terms of the distance between identical features in an array.  The current unit for this distance is “nanometer”, i.e.  a billionth of a meter. The leading edge for productions semiconductor chips today is 10 nanometers.

Moore’s law depends on shrinking the size of the chips while increasing the number of transistors on the chip which increases processing power. Conventional wisdom was that it wouldn’t be possible to push the FinFET technology (which underlies chip manufacturing today) to much smaller chips without losing efficiency. Thus, the comments about the end of Moore’s Law.

However, IBM along with its partners have now developed a process around the Stacked Nanosheet Gate-All-Around Transistor.  This allows eventually building 5 nm chips with improved efficiency, which could not be achieved with FinFETs. The details of the process exceed the scope of this paper. (Those interested can start here[3].) The chart below provides a simplified view of the new IBM process compared with the existing industry standard 10 nm process.


Chart 1 This chart is an adaption of a copyrighted IBM chart.
There are several items of note. IBM's  new chips orient transistors horizontally versus today’s vertical arrangement. This allows transistors to be stacked and have more on each chip. Also, IBM chips use a new way to form the sheet material that is much more efficient in power consumption. It delivers a 75% saving in power compared to existing 10 nm chip architectures.  Finally, the new sheet formation process allows continuous fine-tuning for power and performance of specific circuits during manufacturing. Something not possible with FinFET technology

In summary, it appears to us that the IBM consortium has breathed new life into Moore’s law. With this new architecture, it looks to be applicable for the next decade or so just when many were pronouncing the law dead. However, we expect the interest and investments in such new technologies as quantum, data-centric computing and other approaches to grow.

[1] Publication in 1974 of a paper by Robert Dennard et al on MOSFET scaling rules for improving transistor density. See http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.334.2417
[2] Not actually a law, it was a prediction about how the semiconductor industry would evolve in terms of density and cost per transistor.

Ptak Associates Tech Blog: Do two positive quarters signal a major turnaround...

Ptak Associates Tech Blog: Do two positive quarters signal a major turnaround...: By Bill Moran and Rich Ptak Although we don’t usually cover IBM storage, it’s worth calling attention to what appears to be a significa...

Thursday, August 10, 2017

Do two positive quarters signal a major turnaround for IBM Storage?

By Bill Moran and Rich Ptak


Although we don’t usually cover IBM storage, it’s worth calling attention to what appears to be a significant positive development.   Ed Walsh joined IBM as general manager of IBM Storage and Software Defined Infrastructure on July 11 of 2016.  He joined IBM from Catalogic Software, where he was CEO since 2014.  IBM Storage which had endured 21 consecutive quarters of declining revenue has turned a corner.  Revenue results since then appear below.

Storage Revenue by Quarter

1Q15 
2Q15 
3Q15
4Q15
1Q16
2Q16
3Q16
4Q16
1Q17
2Q17
-4%        
-14%
-7%
-7%
-6%
-13%
-9%
-10%
+7%
+8%
The change represents a dramatic 17-point swing from -10% in 4Q16 to a positive 7% growth in 1Q17. Growth that continued with another 2Q17 revenue increase of 8%.

With corporate IBM posting 20 or so quarters of declining revenues, IBM Storage reversing the trend by increasing revenue is great news. Storage requires proper investments to maintain such growth. Recent indicators, e.g. announcement of a successful collaboration with Sony using sputtered[1] magnetic tape to advance toward a dramatic increase in tape storage capacities (to 330 TB), suggests they will get what’s needed. And, IBM corporate will shift focus to other problem areas.

We expect IBM storage customers to feel reassured about existing IBM storage investments and benefits. They will view continued investment in and growth with IBM storage as good business sense. 

We fully understand that the storage marketplace remains intensely competitive. We recognize two-quarters of growth doesn’t guarantee success. Any benefits IBM enjoyed from the confusion resulting from the EMC/Dell merger, will disappear. The IBM Storage team will need to remain very motivated and highly competitive.

We are comfortable ending on a positive note. Clearly, IBM management were hoping for exactly what Ed Walsh and his team are delivering. In July alone, they made significant storage announcements, one was a new all flash solution for Exabyte Data analysis for Hortonworks[2]. The other was about a family of new flash arrays[3]. One model, when attached to the new z14 mainframe, delivers less than 20 microsecond response times. With more new offerings coming in 2H17, we look forward to 3Q17 revenue numbers to see if the trend continues. We’re inclined to think it will.




[1] The word “sputtered” is not a misprint. The new tape format is exactly that. It is a major breakthrough in tape technology. Google it for more information.

Sunday, July 16, 2017

IBM z14 Mainframe = Trust and Security Benchmark

By Rich Ptak

         Figure 1 z14 Design Goals        (Image courtesy of IBM, Inc.)
IBM's introduction of the z14, the next generation mainframe raises the bar not only for enterprise security, scalability and performance, but also addresses the pricing issues. The first three with pervasive encryption and technological innovation. The latter with highly flexible container-based pricing models. 

In their announcement details, IBM focused on enterprise and business relevance of the z14.
There are too many new features, capabilities, and innovative aspects to cover in one article.
We will highlight the design goals and provide a quick overview of the perennially interesting new pricing models. Then, look at the Open Enterprise Cloud aspects in a little more detail.

It's the z14 For Trusted Computing - Overview

The amount of business-critical data collected for rapid analysis and feedback continues to explode. Digital transformation is well-on its way to reality for enterprises of all sizes. Data sharing includes an increasing number of partners and customers. The issues around data security, data integrity, data authentication, and the risk of compromise become of increasing concern. At the same time, an operating model built on the hybrid cloud (with collocation, shared infrastructure, multi-tenancy, etc.) is clearly establishing itself as the preferred enterprise computing infrastructure model for the foreseeable future. This results in enormous pressures on existing security and data handling approaches to adapt and change to be more innovative and reliable.

In the increasingly interconnected, interactive world, trust, security, risk reduction and management to serve are critically important. It is such an operating environment that IBM aims to serve as it introduces the z14, the latest generation of mainframe computing.

So, IBM operated with three basic design goals and one major pricing innovation for the z14.
The design goals (see Figure 1) first:
  1. A new security model - pervasive encryption as the new standard for data protection and processing with no changes to apps or impact on SLA's - the security perimeter extends from the center to the edge - designed-for security, processing speed and power; the most efficiently secure mainframe ever. 
  2. Fully leverage continuous, in-built intelligence - complement and extend human-machine interaction with direct application of analytics and machine learning capabilities to data where it resides - leverage continuous intelligence across all enterprise operations.
  3. Provide the most open enterprise operating environment - new hardware, open standard firmware, operating system, middleware and tooling that simplifies systems management for admins with minimal IBM z knowledge - more Open Source software supports agile computing, e.g. leverage and extend existing API's as service offerings; easier scaling of cloud services.

Next, pricing innovation:

After some extensive research with customers, IBM is introducing three new pricing models.
The goal is to provide increased operational flexibility with prices that are significantly more
competitive and attractive for modern digital workloads. Container Pricing for IBM z is designed
to provide "simplified software pricing for qualified solutions, combining flexible deployment
options with competitive economics that are directly relevant to those solutions." We provide
some details later. First, a look at the Open and Connected aspect of the z14.

Open and Connected

Today's market demands open, agile operating environments, and services with new or
extended capabilities being introduced rapidly and seamlessly. All to be delivered through an
agile, open enterprise cloud. The z14 software environment is designed to those expectations.
Advanced DevOps tools that leverage new and existing APIs can cut service build times by
90%. To speed innovation, IBM's extensive ecosystem of partners are developing and
delivering thousands of enterprise-focused, open source software packages to support the
mainframe in accelerating the "delivery of new digital services through the cloud." Let's look at
this a little more closely.

The new z14 is about leveraging APIs to speed development and ease access to mainframe
capabilities. The goal is to make the efforts of developers and users to exploit the powers of
the mainframe to be easier to access, simpler to use and more quickly deliverable to the
market. This is to be achieved with new hardware, firmware, operating system, middleware
and tooling that simplifies systems management tasks. These also make the process easier for
system administrators with minimal IBM z System experience and knowledge.

The procedure breaks down into four tasks:

  1. Discover - leverage existing investments by helping developers to quickly, automatically discover existing applications and services that can then be converted to API services. 
  2. Understand -  prior to going into production or implementing application changes, identify the dependencies and interactions between the applications and API's to identify how they are affected by any changes. Know where and what an API touches to avoid down time and re-working of changes. It also minimizes the risk of removing protection of critical data by exposing an API. 
  3. Connect - provide easy, automated creation of RESTful services based on industry standard tooling to rapidly create new business value, e.g. link a vacation search to destination appropriate clothing, hotels, interesting sites, etc. Or, associate an order for heavy equipment to a link that suggests purchasing insurance, maintenance, installation or operating services. 
  4. Analyze - use operational analytics and data collection to create an enterprise view of the mainframe and the surrounding operational environment. Integrate the z System data with data from over 140 different data sources in any format. Search, analyze and create a visual representation of service activities and interactions using SIEM tools, such as Splunk or open source Elasticsearch. This helps in early identification of potential problem areas such as performance bottlenecks or operational conflicts.

New capabilities dramatically increase the performance and scalability to already impressive
mainframe abilities. These include such new capabilities as zHyperLink a new direct connect,
short-distance link. It is designed for low latency connectivity between the z14 and FICON
storage systems. It can lower latency by up to 10x which can reduce response time up to 50%
in I/O sensitive workloads, without any code changes. The z14 has available, as a purchasable
option, Automatic Binary Optimizer for z/OS(r), which will automatically optimize binary code for
COBOL applications which can reduce their CPU usage by 80% without a recompilation. One
z14 can scale out to support an impressive 2 million Docker containers. Now, let's look at
pricing.

Container Pricing for IBM z

Any mainframe discussion is bound to include a discussion of pricing policies, management,
and control. Customers want predictability - to know what the bill will be. They want
transparency - knowing how billing is calculated. They want visibility - to understand the
impact of changing or moving workloads. They want managerial flexibility - ability to adjust
workload processing and scheduling to balance their needs with computing costs.

IBM's solution is the concept of Container Pricing for IBM z, which provides line-of-sight pricing
to make the true cost highly visible. It applies to a collection of software collocated in a single
container. It determines a fixed price which applies to that single container[1] of software with no impact to the pricing of anything external to the container.



[1] A container is a collection of software treated for pricing purposes as a single item. The collection is priced separately and independently of any other software on the system.

A container pricing solution can be within a single logical partition or a collection of partitions.
Multiple, collocated and/or stacked containers are permitted. Separate containers with different
pricing models and metrics can reside in the same logical partition. Container deployment is
flexible to allow the best technical fit, independent of the costs. Three types of Container
Pricing solutions are offered now:
  1. Application Development and Test solution (DevTest) - provides DevTest capacity that can be increased (up to 3x) at no additional MLC cost. Clients choose the desired multiplier and set the reference point for MLC and OTC software. Additional DevOps tooling with unique, discounted prices are available. 
  2. New Application solutions - special, competitive pricing for those adding a new z/OS workload to existing environments. There is no impact on existing workload prices. The container size determines the billing for capacity-priced IBM software.Payments 
  3. Pricing solution - offers on-premise, Payments-as-a-Service on z/OS based on IBM Financial Transaction Manager. It applies to software or software plus hardware combinations. 
This is a simplified review of the new model. Contact IBM for more detailed information. IBM
will be refining and adding models to meet customer needs. Moving on to the other design goals.

Trust + Security thru Pervasive Encryption

Data and application security in enterprise IT have taken a beating in the last few years. Traditional security techniques and barriers have fallen victim to numerous attacks as well as rapidly evolving threats and scams. Successful attacks and breaches came from sophisticated external criminals as well as maliciously or accidentally by insiders. Victims include large, sophisticated financial institutions to national governments and ministries. Even blockchain ledgers have proven vulnerable to weak implementations and clever hackers.

With data widely recognized as an asset of escalating value, the risks and costs of such breaches increases. Traditional security methods focused on trying to prevent successful intrusions or minimizing damage with selective encryption, rapid detection, and blocking. Selective data encryption proved too expensive, resource intensive and inconsistent in application. And, significant risks remain when leaving some data un- or weakly protected as hackers and intruders became more sophisticated. Also, new policies or evolving compliance requirements can make critical once non-critical data, further weakening selective methods.

IBM's solution was to design the z14 with hardware technology and software protections that make pervasive encryption from the edge to the center including the network affordable, efficient and rapid. All data is encrypted all the time without requiring any changes to applications and without impacting Service Level Agreements (SLA's).

Application of Machine Learning

Successfully leveraging artificial intelligence (AI) in the enterprises had been an elusive goal
for decades. Early attempts were frustrated by limitations in expertise, processing power, high
costs and the sheer amount of effort required to build and test models.

Today, the maturation and automation of modeling techniques along with improvements in
infrastructure and technology have allowed AI, more accurately described as machine learning,
to come into its own in the enterprise. Examples in the z14 include optimized instructions,
faster processing of Java code, and improved math libraries that speed and improve analytics.
The 32TB of memory means the z14 can process more information and analyze larger
workloads and in-memory databases in real-time. The results come in the form of prompt
availability of actionable business insights that result in better customer services. The
announcement contains much more about machine learning applications as well Blockchain
capabilities. Topics for future coverage.

The Final Word

The new z14 is an impressive and worthy addition to the IBM mainframe family. It promises
"Trusted" computing on the platform that has been the benchmark for processor security. That
is a much-desired deliverable in a highly integrated, totally connected, rapidly evolving world of
digital enterprise. There are many more attractive features to the new z14. These include
unique to IBM Blockchain services which provide significant protection against fraud. There's
the ability to rapidly build microservices choosing from over 20 different languages and
databases to use. There's the free access to the mainframe for those interested in testing the
ease of use features or expanding their mainframe skillset. (See https://ibm.biz/ibmztrial).

By delivering efficient, affordable, speedy 100% end-to-end encryption of all application and
data base data it pushes infrastructure boundaries to achieve a uniquely secure environment;
without requiring any changes to applications, services or data. IBM has also implemented
unique encryption key protection that removes any risk of it being exposed. To do so without
changing or impacting the ability SLA's is remarkable. IBM estimated encryption overhead at
"low-to-mid" single digits.

IBM's focus on automating and facilitating the utilization and optimization of API services is a
very smart move on their part. An on-going 'critique' of the mainframe has been that it is
inaccessible, living and operating in its own isolation. True in the past, the last few years have
seen a dramatic alteration with the emergence of the "Open, Connected and Innovative"
mainframe. The change has been rapid and significant.

The significant impact of the introduction of Linux on Z and the proliferation of numerous Open
Standard solutions, APIs, tools and interfaces cannot be ignored. The introduction and
movement of numerous Open Stack products to the mainframe along with the addition of agile,
Open Source DevOps tools and APIs have made the mainframe's extensive capabilities easier
to access and faster to exploit by a much wider audience. This is reflected in the growth of the
highly diverse ecosystem of mainframe partners, ISVs and developers working with IBM. The
z14 looks to accelerate that process.

The mainframe, IBM's longest running product, has seen its ups and downs over the last 50+
years. Anticipation and predictions of its death have filled column space of way too much IT
commentary, stories and speculation. The z14 fills a well-defined, valuable place in the IT
infrastructure.

Friday, July 14, 2017

IBM and Nutanix deliver no-compromise, on-premise Cloud computing with IBM Hyperconverged Systems powered by Nutanix

By Rich Ptak

Figure 1 IBM CS822  (Photo courtesy of IBM, Inc.)

Congratulations to IBM[1] and Nutanix[2] on their July 11th announcement of the industry’sfirst hyperconverged system that combines Nutanix software with POWER8-based systems (IBM CS821, IBM CS822). They are delivering two significant innovations:
  1. Immediate access to a fully-configured, full stack workload-optimized system with servers designed for data and high-performance workloads, e.g. high-volume transaction and cognitive analytics. This includes scale-out Linux workloads like IBM WebSphere® Application Server, NGINIX, IBM Big Insights/Hadoop, etc.
  2. Vastly simplified, automated implementation of on-premise cloud-like operation. Nutanix’s world-class Enterprise Cloud Platform[3] makes cloud creation transparent as it simplifies operations and management with one-click access, operation, and management in an on-premise cloud-like environment.

Configuring the optimal combination of compute infrastructure elements (processor, storage, network, operating software, etc.) for a workload has been a challenge forever. The perennial trade-off has been between the heavy burden and expertise required to design a system for optimal workload performance; and the alternative of adapting the workload to an off-the-shelf system. Custom configurations involve a resource intensive, manual process requiring significant expertise with the significant downsides of cost, time and the need for specialized support. The standard alternative sacrifices performance, capacity, scalability or other features, for a lower cost, immediate availability and standard support. In today’s rapidly evolving, highly competitive market, such compromising may yield short-term advantage, but will more likely result in long-term problems.

A cloud-based solution would be an alternative, for those with the necessary expertise in cloud infrastructure design, configuration, management, etc. Or, a willingness to depend upon cloud provider expertise. Not to worry. Just last May, IBM and Nutanix announced plans to attack the problem head-on with a multi-year initiative to provide an integrated solution that combines Nutanix’s Enterprise Cloud Platform software with IBM’s Hyperconverged Systems optimized for specific enterprise workloads.

The first results are seen in these turn-key hyperconverged fully-scalable, on-premise cloud systems. They are impressive. There’s a lot more to the announcement. So, talk to IBM to get the full details. We expect customers will agree.

Monday, July 10, 2017

Compuware Further Boosts Mainframe Agility with Topaz for Total Test Enhancements and Integrations with Leading DevOps Tools

By Rich Ptak



Figure 1 Topaz for Total Test Speeds and Simplifies COBOL Unit Testing
Image courtesy of Compuware


 It's a new quarter and time for a Compuware mainframe product announcement. This time the focus is on enhancements to Topaz for Total Test. As you may recall, we last commented on Topaz for Total Test's powerful automation capabilities for application test creation, implementation, execution, and cleanup at ist's introduction last January[1].See Figure 1 above.

 Earlier announcements have addressed such topics as Source Code Management[2], Release Automation and Application Deployment and Application Audit, which increases overall cybersecurity and compliance with automated auditing of user behavior with applications. Integration with SIEM tools such as Splunk[3] allows the user to get a cross-enterprise view that speeds identification and detection of non-compliant and security threatening behavior by users. 

Topaz for Total Test, the subject of this commentary, addresses problems of COBOL code change management with groundbreaking automation and innovations in COBOL code testing. Given the abject failure of re-platforming initiatives, large enterprises hoping to avoid digital irrelevance must aggressively modernize their mainframe DevOps practices. Key to the modernization and ‘de-legacing’ of mainframe application is the adoption of unit testing for COBOL code that is equivalent to and well-integrated with unit testing as practiced across the rest of the enterprise codebase. That is exactly the challenge Compuware addresses with Topaz for Total Test.

Compuware has committed to build on its solution base using agile, continuous, modern processes to deliver significant enhancements and extensions. In fulfillment of that commitment, they are developing new DevOps Toolchain integrations and extended support for DB2 SQL. Here is what they are bringing to market.

What’s new?


Compuware made an impressive start in January with the initial release of Topaz for Total Test, which enables developers at all skill levels to perform unit testing of COBOL code similar to how it is done for other programming languages (Java, PHP, etc.). Program Stubs were also a significant and highly popular innovation. Stubs allow sub-program calls to be disconnected from the main program. Therefore, the subprograms can be tested independently of the main program. Data Stubs eliminate the need to access data files or DB2 Tables. Testing becomes much easier, less complicated, less risky and complete considerably faster. Testing can be repeated without disrupting the production environment, thereby significantly increasing operational flexibility. It was no surprise that customers responded enthusiastically by using stubs extensively and quickly identifying specific extensions to make the product even more attractive.

 
Compuware quickly moved to explore the possibilities for further automation of the unit test process. Developers, like all skilled craftsmen, have favored tools. For developers, these include Jenkins (toolchain management), SonarQube (quality control) and Compuware’s own ISPW (source code management and deployment).

Compuware recognized the opportunity to completely automate the DevOps processes of Build – Test – Deploy. They also noted that the ability to test independently of the main program and without impacting operations was highly valuable as it simplified a frustrating, time-consuming task. Further, data stubbing could be used in other areas to eliminate or reduce dependencies to further strengthen, simplify and speed testing. This release responds to those requests. The results are the enhancements included in the announcement. They are:
  • Topaz for Total Test integration with Jenkins which enables COBOL unit testing to be automatically triggered as part of a DevOps toolchain and/or continuous delivery process. The result is a significant increase in efficiency.  
  • Topaz for Total Test integration with SonarSource’s SonarQube ensures quality trends are visible throughout the development process by displaying pass/fail testing results along with all cross-platform DevOps activities. 
  • Topaz for Total Test integration with Compuware ISPW tightly couples test cases with source code to enable the sharing of test assets, enhanced workflow and the enforcement of testing policies as part of the DevOps toolchain.
  • New “stubbing” for DB2 databases allows developers to run unit tests without requiring an active connection to a live DB2 database. This is huge. Testing can be done against real data without impacting or risking corruption of the production data base. With stubbing, Topaz for Total Test can test code processing most types of mainframe data. The unique capability for stubbing of DB2, VSAM, and QSAM data types means that creating repeatable tests is much easier. Data stubs can be created automatically with no re-compilation needed. 

There’s still more in the announcement. The DB2 data used to make SQL statement stubs can be collected automatically, in real-time from on-line test databases. These data stubs can be saved and used to create and run new scenarios for use by other testers. Data stubs can be reused or overwritten by multiple testing programs. Decoupling code into subprograms allows Unit testing to be done in smaller increments, speeding results, simplifying testing and allowing for more granular analysis and better testing. All this means testing can be done without requiring a large system for testing. Testing can be done on-line with no risk to the production database. Job Control Language (JCL) can be created and reused from Profiles, eliminating the need to recreate them every time. 

The Final Word
Compuware is aggressively pursuing a strategy directed at “Mainstreaming the Mainframe.” Their strategy recognizes and is dedicated to overcoming structural and operational issues that make mainframe utilization and COBOL code maintenance a complex, slow and intimidating task, especially for those new to the mainframe.

They do so by delivering “big step” IT tools that introduce the latest new-to-the-mainframe capabilities, such as automated unit testing. But, they also extend and enhance existing solutions by automating functions or processes, providing interesting product integrations and extending APIs to simplify or ease time-consuming mainframe tasks that annoy admin and operations staffs. To accomplish this, Compuware has employed and made contributions in visualization, code analysis, behavior auditing, automated unit testing, operations management, etc.  

Topaz for Total Test provides positive proof of Compuware’s success as it benefits both IT and production staffs. IT staff benefit from access to familiar, modern tools and more efficient processes. IT productivity and performance benefit from increased automation. Faster collection of test data by exploiting Compuware’s Xpediter is one example. The extensive use of automation in test creation (such as collecting test data) and execution improves the quality and depth of testing. Integrations with Jenkins, SonarQube, and ISPW further empower less experienced mainframe developers to work on multi-tier apps. The overall result is that program updates, changes and improvements move more quickly through the DevOps process to get higher quality code into the production environment.

Operations benefits as both customers and users see improvements. Users benefit from better quality code with few problems and faster introduction of changes to meet business and operational needs. Customer satisfaction improves when they get the benefits of updated and modified code with fewer problems.

This is the 11th consecutive quarter that Compuware has delivered on its “Mainstreaming the Mainframe” commitment to improve and make more attractive the Mainframe ecosystem. Figure 2 at right summarizes their path to this point.



Figure 2 Compuware Delivery Record to Date
Image courtesy of Compuware

Their performance to-date has been impressive by any measure. And, from what we’ve been told and heard from them, they fully expect to continue to deliver at an equivalent pace and scale for the foreseeable future.

We congratulate Compuware on their success so far, as well as their commitment to the future. Compuware’s efforts have positively impacted the mainframe market, to the benefit of everyone involved in that market whether partner, customer, service provider or vendor. Look at what they’ve done; see if you don’t agree.




[2] For more details on these and other topics see: http://www.ptakassociates.com/content/
[3] Read about the full range of Splunk products here: https://www.splunk.com/