Posts Tagged ‘IBM’

IBM Suggests Astounding Productivity with Cloud Pak for Automation

November 25, 2019

DancingDinosaur thought IBM would not introduce another Cloud Pak until after the holidays, but I was wrong. Last week IBM launched Cloud Pak for security. According to IBM it helps an organization uncover threats, make more informed risk-based decisions, and prioritize your team’s time. 

More specifically, it connects the organization’s existing data sources to generate deeper insights. In the process you can access IBM and third-party tools to search for threats across any cloud or on-premises location. Quickly orchestrate actions and responses to those threats  while leaving your data where it is.

DancingDinosaur’s only disappointment in the IBM’s new security cloud pak as with other IBM Cloud Paks is that it runs only on Linux. That means it doesn’t run RACF, the legendary IBM access control tool for zOS. IBM’s Cloud Paks reportedly run on z Systems, but only those running Linux. Not sure how IBM can finesse this particular issue. 

Of the 5 original IBM Cloud Paks (application, data, integration, multicloud mgt, and automation) only one offers the kind of payback that will wow top c-level execs; automation.  Find Cloud Park for Automation here.

To date, IBM reports  over 5000 customers have used IBM Digital Business Automation to run their digital business. At the same time, IBM claims successful digitization has increased organizational scale and fueled growth of knowledge work.

McKinsey & Company notes that such workers spend up to 28 hours each week on low value work. IBM’s goal with digital business automation is to bring digital scale to knowledge work and free these workers to work on high value tasks.

Such tasks include collaborating and using creativity to come up with new ideas or meeting and building relationships with clients or resolving issues and exceptions. By automating these tasks the payoff, says IBM, can be staggering simply  by applying intelligent automation.

“We can reclaim 120 billion hours a year  spent by knowledge workers on low value work by using intelligent automation,” declares IBM.  So what value can you reclaim over the course of the year for your operation with, say, 100 knowledge workers, earning, maybe, $22 per hour, or maybe 1000 workers earning $35/hr. You can do the math. 

As you would expect,  automation is the critical component of this particular Cloud Pak. The main targets for enhancement or assistance among the rather broad category of knowledge workers are administrative/departmental work and expert work, which includes cross enterprise work.  IBM offers vendor management as one example.

The goal is to digitize core services by automating at scale and building low code/no code apps for your knowledge workers. For what IBM refers to as digital workers, who are key to this plan, the company wants to free them for higher value work. IBM’s example of such an expert worker would be a loan officer. 

Central to IBM’s Cloud Pak for Automation is what IBM calls its Intelligent Automation Platform. Some of this is here now, according to the company, with more coming in the future. Here now is the ability to create apps using low code tooling, reuse assets from business automation workflow, and create new UI assets.

Coming up in some unspecified timeframe is the ability to enable  digital workers to automate job roles, define and create content services to enable intelligent capture and extraction, and finally to envision and create decision services to offload and automate routine decisions.

Are your current and would-be knowledge workers ready to contribute or participate in this scheme? Maybe for some. it depends for others. To capture those billions of hours of increased productivity, however, they will have to step up to it. But you can be pretty sure IBM will do it for you if you ask.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/ 

 

IBM Cloud Pak Rollouts Continue

November 14, 2019

IBM Cloud Paks have emerged as a key strategy by the company to grow not just its cloud, but more importantly, its hybrid cloud business. For the past year or so, IBM shifted its emphasis from clouds to hybrid clouds. No doubt this is driven by its realization that its enterprise clients are adopting multiple clouds, necessitating the hybrid cloud.

The company is counting on success in hybrid clouds.  For years IBM has scrambled to claw a place for itself among the top cloud players but from the time DancingDinosaur has tracked IBM’s cloud presence it has never risen higher than third. In 2019, the top cloud providers are AWS, Microsoft, Google, IBM, Oracle, Alibaba, with IBM slipping to fourth in one analyst’s ranking.

Hybrid clouds, over time, can change the dynamics of the market. It has not, however, changed things much according to a ranking from Datamation. “There are too many variables to strictly rank hybrid cloud providers,” notes Datamation. With that said, Datamation still ranked them starting with  Amazon’s Amazon Web Services (AWS), which remains the unquestioned leader of the business with twice the market share as its next leading competitor, Microsoft/Azure, and followed by IBM. The company is counting on its Red Hat acquisition, which includes OpenShift along with Enterprise Linux, to alter its market standing.. 

The hybrid cloud segment certainly encompasses a wider range of customer needs, so there are ways IBM can work Red Hat to give it some advantages in pricing and packaging, which it has already signaled it can and will do, starting with OpenShift. DancingDinosaur doubts it will overtake AWS outright, but as noted above, hybrid clouds are a different beast. So don’t rule out IBM in the hybrid cloud market.

Another thing that may give IBM an edge in hybrid clouds among its enterprise customers are its Cloud Paks.  As IBM describes them Cloud Paks are enterprise-ready, containerized software that give organizations an open, faster and more secure way to move core business applications to any cloud. Each IBM Cloud Pak runs on Red Hat OpenShift, IBM Cloud, and Red Hat Enterprise Linux. 

Each pak includes containerized IBM middleware and common software services for development and management. Also included is a common integration layer designed to reduce development time by up to 84 percent and operational expenses by up to 75 percent, according to IBM.

Cloud Paks, IBM continues,, enable you to easily deploy modern enterprise software either on-premises, in the cloud, or with pre-integrated systems and quickly bring workloads to production by seamlessly leveraging Kubernetes as the container management framework supporting production-level qualities of service and end-to-end lifecycle management. This gives organizations an open, faster, more secure way to move core business applications to any cloud.

When IBM introduced Cloud Paks a few weeks ago they planned a suite of five Cloud Paks:  

  • Application
  • Data
  • Integration
  • Automation
  • Multi Cloud mgt

Don’t be surprised as hybrid cloud usage evolves if even more Cloud Paks eventually appear. It becomes an opportunity for IBM to bundle together more of its existing tools and products and send them to the cloud too.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/ 

October 8, 2019

z15 LinuxONE III for Hybrid Cloud

 

It didn’t take long following the introduction of the z15 for a LinuxONE to arrive. Meet the LinuxONE III, a z15 machine with dedicated built-in Linux. And it comes with the primary goodies that the z15 offers: automatic pervasive compression of everything along with a closely related privacy capability, Data Passport.

3-frame LinuxONE III

Z-quality security, privacy, and availability, it turns out, has become central to the mission of the LinuxONE III.The reason is simple: Cloud. According to IBM, only 20% of workloads have been moved to cloud. Why? Companies need assurance that their data privacy and security will not be breached. To many IT pros and business executives, the cloud remains the wild, wild west where bad guys roam looking to steal whatever they can.

IBM is touting the LinuxONE III, which is built on its newly introduced z15, for hybrid clouds. The company has been preaching the gospel of clouds and, particularly, hybrid clouds for several years, which was its primary reason for acquiring Red Hat. Red Hat Linux is built into the LinuxONE III, probably its first formal appearance since IBM closed its acquisition of Red Hat this spring. 

With Red Hat and z15 IBM is aiming to cash in on what it sees as a big opportunity in hybrid clouds. While the Cloud brings the promise of flexibility, agility and openness, only 20% of workloads have been moved to cloud, notes IBM. Why? Companies need assurance that their data privacy and security will not be breached. LinuxONE III also promises cloud native development.

By integrating the new IBM LinuxONE III as a key element in an organization’s hybrid cloud strategy, it adds another level of security and stability and availability to its cloud infrastructure. It gives the organization both agile deployment and unbeatable levels of uptime, reliability, and security. While the cloud already offers appealing flexibility and costs, the last three capabilities–uptime, reliability, security–are not usually associated with cloud computing. By security, IBM means 100% data encryption automatically, from the moment the data arrives or is created. And it remains encrypted for the rest of its life, at rest or in transit.

Are those capabilities important? You bet. A Harris study commissioned by IBM found that 64 percent of all consumers have opted not to work with a business out of concerns over whether that business could keep their data secure. However, that same study found 76 percent of respondents would be more willing to share personal information if there was a way to fully take back and retrieve that data at any time. Thus the importance of the z15’s pervasive encryption and the new data passports.

IBM has previously brought out its latest z running dedicated Linux. Initially it was a way to expand the z market through a reduced cost z.  DancingDinosaur doesn’t know the cost of the LinuxONE III. In the past they have been discounted but given the $34 billion IBM spent to acquire Red Hat the new machines might not be such a bargain this time.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/ 

IBM Introduces 53 Qubit Quantum Machine

September 23, 2019

IBM made two major system announcements within just a couple of weeks: On Sept. 18 IBM announced a 53 qubit guantum machine. The week before, IBM introduced its latest mainframe, the z15. Already buzz is circulating of a z16 in two years, about a normal release cycle for the next generation of  an IBM mainframe. 

Quantum computer up close
IBM’s largest quantum machine at 53 qubits

Along with the 53 qubit machine IBM announced the opening of a Quantum Computation Center in New York state. The new center expands, according to IBM, its fleet of quantum computing systems for commercial and research activity that exist beyond the confines of experimental lab environments. IBM’s offerings run from 5 to 10 to 20 to, now, 53 qubits. These are actual quantum machines hosted by IBM in the cloud, not just simulations. 

The IBM Quantum Computation Center will support the growing needs of a community of over 150,000 registered users and nearly 80 commercial clients, academic institutions and research laboratories to advance quantum computing and explore practical applications. To date, notes IBM, this  global community of users have run more than 14 million experiments on IBM’s quantum computers through the cloud since 2016, and published more than 200 scientific papers. To meet growing demand for access to real quantum hardware, ten quantum computing systems are now online through IBM’s Quantum Computation Center. The fleet is composed of five 20-qubit systems, one 14-qubit system, and four 5-qubit systems. Five of the systems now have a quantum volume of 16 – a measure of the power of a quantum computer used by IBM demonstrating a new sustained performance milestone.

IBM’s quantum systems are optimized for the reliability and reproducibility of programmable multi-qubit operations. Due to these factors, the systems enable state-of-the-art quantum computational research with 95 percent availability, according to the company.

Within one month, IBM’s commercially available quantum fleet will grow to 14 systems, including the new 53-qubit quantum computer, the single largest universal quantum system made available for external access in the industry to date. The new system offers a larger lattice and gives users the ability to run even more complex entanglement and connectivity experiments. Industry observers note that serious work requires a minimum of 200 qubits, probably just a couple more product intros away. 

Advances in quantum computing could open the door to future scientific discoveries such as new medicines and materials, vast improvements in the optimization of supply chains, and new ways computers to model financial data to make better investments. Examples of IBM’s  work with clients and partners, include:

  • J.P. Morgan Chase and IBM posted on arXiv,  Option Pricing using Quantum Computers, a methodology to price financial options and portfolios of such options, on a gate-based quantum computer. This resulted in an algorithm that provides a quadratic speedup, i.e. whereby classically computers need millions of samples, this methodology requires only a few thousands of samples to achieve the same result, It allows financial analysts to perform the option pricing and risk analysis in near real time. The implementation is available as open source in Qiskit Finance. 
  • Mitsubishi Chemical, Keio University and IBM simulated the initial steps of the reaction mechanism between lithium and oxygen in lithium-air batteries. Also available on arXiv,  this represents a first step in modeling the entire lithium-oxygen reaction on a quantum computer. Better understanding of this interaction could lead to more efficient batteries for mobile devices or automotive vehicles.

In the meantime IBM continues to simulate quantum algorithms on conventional supercomputers. According to one 2-year old report: at roughly 50 qubits, existing methods for calculating quantum amplitudes require either too much computation to be practical, or more memory than is available on any existing supercomputer, or both. You can bet that IBM or somebody else will push beyond 53 qubits pretty quickly. Google already claims a 72-qubit device, but it hasn’t let outsiders run programs on it. IBM has been making quantum available via the cloud since 2016. Other companies putting quantum computers in the cloud, include IBM’s Quantum Computation Center.IBM’s Quantum Computation Center. Others include  Rigetti Computing,  and Canada’s D-Wave

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/ 

IBM Advances Commercial Quantum Computing

August 7, 2019

The reason IBM and others are so eager for quantum computing is simple: money. Recent efforts have demonstrated that quantum analytics can process massive amounts of transactions quickly and accurately, as much as nearly $70 Trillion last year, according to the World Bank.

“These are enormous amounts of money,” says mathematician Cornelis Oosterlee of Centrum Wiskunde & Informatica, a national research institute in the Netherlands for a piece in Wired Magazine. “Some single trades involve numbers that are scary to imagine”—part of a company’s pension fund, say, or a university endowment, he continues.

Of course, this isn’t exactly new. Large organizations with access to huge amounts of resources devote inordinate quantities of those resources in an effort to predict how much their assets will be worth in the future.  If they could do this modeling faster or more accurately or more efficiently, maybe just shaving off a few seconds here or there; well you can do the arithmetic.

Today these calculations are expensive to run, requiring either an in-house supercomputer or two or a big chunk of cloud computing processors and time. But if or when quantum computing could deliver on some of its theoretical promise to drive these analyses faster, more accurately, more efficiently and cheaper that’s something IBM could build into the next generation of systems.. 

And it is not just IBM. From Google on down to startups, developers are working on machines that could one day beat conventional computers at various tasks, such as classifying data through machine learning or inventing new drugs—and running complex financial calculations. In a step toward delivering on that promise, researchers affiliated with IBM and J.P. Morgan recently figured out how to run a simplified risk calculation on an actual quantum computer.

Using one of IBM’s machines, located in Yorktown Heights, New York, the researchers demonstrated they could simulate the future value of a financial product called an option. Currently, many banks use what’s called  the Monte Carlo method to simulate prices of all sorts of financial instruments. In essence, the Monte Carlo method models the future as a series of forks in the road. A company might go under; it might not. President Trump might start a trade war; he might not. Analysts estimate the likelihood of such scenarios, then generate millions of alternate futures at random. To predict the value of a financial asset, they produce a weighted average of these millions of possible outcomes.

Quantum computers are particularly well suited to this sort of probabilistic calculation, says Stefan Woerner, who led the IBM team. Classical (or conventional) computers—the kind most of us use—are designed to manipulate bits. Bits are binary, having a value of either 0 or 1. Quantum computers, on the other hand, manipulate qubits, which represent an in-between state. A qubit is like a coin flipping in the air—neither heads nor tails, neither 0 nor 1 but some probability of being one or the other. And because a qubit has unpredictability built in, it promises to  be a natural tool for simulating uncertain outcomes.

Woerner and his colleagues ran their Monte Carlo calculations using three of the 20 qubits available on their quantum machine. The experiment was too simplistic to be useful commercially, but it’s a promising proof of concept; once bigger and smoother-running quantum computers are available, the researchers hope to execute the algorithm faster than conventional machines.

But this theoretical advantage is just that, theoretical. Existing machines remain too error-ridden to compute consistently, In addition, financial institutions already have ample computing power available, onsite or in the cloud.. And they will have even more as graphics processing units (GPU), which can execute many calculations in parallel, come on line. A quantum computer might well be faster than an individual chip but it’s unclear whether it could beat a fleet of high performance GPUs in a supercomputer.

Still, it’s noteworthy that the IBM team was able to implement the algorithm on actual hardware, says mathematician Ashley Montanaro of the University of Bristol in the UK, who was not involved with the work. Academics first developed the mathematical proofs behind this quantum computing algorithm in 2000, but it remained a theoretical exercise for years. Woerner’s group took a 19-year-old recipe and figured out how to make it quantum-ready on actual quantum hardware.

Now they’re looking to improve their algorithm by using more qubits. The most powerful quantum computers today have fewer than 200 qubits, Practitioners suggest it may take thousands to consistently beat conventional methods.

But demonstrations like Woerner’s, even with their limited scope, are useful in that they apply quantum computers to problems organizationz actually want to solve, And that is what it will take if IBM expects to build quantum computing into a viable commercial business.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at technologywriter.com. 

IBM teams with Cloudera and Hortonworks 

July 11, 2019

Dancing Dinosaur has a friend on the West coast who finally left IBM after years of complaining, swearing never to return, and has been happily working at Cloudera ever since. IBM and Cloudera this week announced a strategic partnership to develop joint go-to-market programs designed to bring advanced data and AI solutions to more organizations across the expansive Apache Hadoop ecosystem.

Graphic representing a single solution for big data analytics

Deploy a single solution for big data

The agreement builds on the long-standing relationship between IBM and Hortonworks, which merged with Cloudera this past January to create integrated solutions for data science and data management. The new agreement builds on the integrated solutions and extends them to include the Cloudera platform. “This should stop the big-data-is-dead thinking that has been cropping up,” he says, putting his best positive spin on the situation.

Unfortunately, my West coast buddy may be back at IBM sooner than he thinks. With IBM finalizing its $34 billion Red Hat acquisition yesterday, it is small additional money to just buy Horton and Cloudera and own them all as a solid big data-cloud capabilities block IBM owns.  

As IBM sees it, the companies have partnered to offer an industry-leading, enterprise-grade Hadoop distribution plus an ecosystem of integrated products and services – all designed to help organizations achieve faster analytic results at scale. As a part of this partnership, IBM promises to:

  • Resell and support of Cloudera products
  • Sell and support of Hortonworks products under a multi-year contract
  • Provide migration assistance to future Cloudera/Hortonworks unity products
  • Deliver the benefits of the combined IBM and Cloudera collaboration and investment in the open source community, along with commitment to better support analytics initiatives from the edge to AI.

IBM also will resell the Cloudera Enterprise Data Hub, Cloudera DataFlow, and Cloudera Data Science Workbench. In response, Cloudera will begin to resell IBM’s Watson Studio and BigSQL.

“By teaming more strategically with IBM we can accelerate data-driven decision making for our joint enterprise customers who want a hybrid and multi-cloud data management solution with common security and governance,” said Scott Andress, Cloudera’s Vice President of Global Channels and Alliances in the announcement. 

Cloudera enables organizations to transform complex data into clear and actionable insights. It delivers an enterprise data cloud for any data, anywhere, from the edge to AI. One obvious question: how long until IBM wants to include Cloudera as part of its own hybrid cloud? 

But IBM isn’t stopping here. It also just announced new storage solutions across AI and big data, modern data protection, hybrid multicloud, and more. These innovations will allow organizations to leverage more heterogeneous data sources and data types for deeper insights from AI and analytics, expand their ability to consolidate rapidly expanding data on IBM’s object storage, and extend modern data protection to support more workloads in hybrid cloud environments.

The key is IBM Spectrum Discover, metadata management software that provides data insight for petabyte-scale unstructured storage. The software connects to IBM Cloud Object Storage and IBM Spectrum Scale, enabling it to rapidly ingest, consolidate, and index metadata for billions of files and objects. It provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. Combining that with Cloudera and Horton on the IBM’s hybrid cloud should give you a powerful data analytics solution. 

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at technologywriter.com. 

 

IBM Pushes Quantum for Business

June 20, 2019

Other major system providers pursuing quantum computing initiatives, but none are pursuing it as methodically or persistently as IBM. In a recent announcement:  IBM’s Institute for Business Value introduced a five-step roadmap to bring quantum computing to your organization.

Into IBM Q computation center: dilution refrigerators with microwave electronics (middle) that provide Q Network cloud access to 20-qubit processor. (Credit: Connie Zhou)

Start by familiarizing yourself with superposition and entanglement, which enable quantum computers to solve problems intractable for today’s conventional computers:

Superposition. A conventional computer uses binary bits that can only depict either 1 or 0. Instead, quantum computers use qubits that can depict a 1 or 0, or any combination by superposition of the qubits’ possible states. This supplies quantum computers with an exponential set of states they can explore to solve certain types of problems better than conventional computers.

Entanglement. In the quantum world, two qubits located even light-years apart can still act in ways that are strongly correlated. Quantum computing takes advantage of this entanglement to encode problems that exploit this correlation between qubits.

The quantum properties of superposition and entanglement enable quantum computers to rapidly explore an enormous set of possibilities to identify an optimal answer that could maximize business value. As future quantum computers can calculate certain answers exponentially faster than today’s conventional machines, they will enable tackling business problems that are exponentially more complex.

Despite conventional computers’ limitations, quantum computers are not expected to replace them in the foreseeable future. Instead, hybrid quantum-conventional architectures are expected to emerge that, in effect, outsource portions of difficult problems to a quantum computer.

Already Quantum computing appears ripe to transform certain industries. For instance, current computational chemistry methods rely heavily on approximation because the exact equations cannot be solved by conventional computers. Similarly, quantum algorithms are expected to deliver accurate simulations of molecules over longer timescales, currently impossible to model precisely. This could enable life-saving drug discoveries and significantly shorten the number of years required to develop complex pharmaceuticals.

Additionally, quantum computing’s anticipated ability to solve today’s impossibly complex logistics problems could produce considerable cost savings and carbon footprint reduction. For example, consider improving the global routes of the trillion-dollar shipping industry (see Dancing Dinosaur’s recent piece on blockchain gaining traction). If quantum computing could improve container utilization and shipping volumes by even a small fraction, this could save shippers hundreds of millions of dollars. To profit from quantum computing’s advantages ahead of competitors, notes IBM, some businesses are developing expertise now to explore which use cases may benefit their own industries as soon as the technology matures.

To stimulate this type of thinking, IBM’s Institute of Business Value has come up with 5 steps to get you started:

  1. Identify your quantum champions. Assign this staff to learn more about the prospective benefits of quantum computing. Just designate some of your leading professionals as quantum champions and charge them with understanding quantum computing, its potential impact on your industry, your competitors’ response, and how your business might benefit. Have these champions report periodically to senior management to educate the organization and align progress to strategic objectives.
  2. Begin identifying quantum computing use cases and associated value propositions. Have your champions identify specific areas where quantum computing could propel your organization ahead of competitors. Have these champions monitor progress in quantum application development to track which use cases may be commercialized sooner. Finally, ensure your quantum exploration links to business results. Then select the most promising quantum computing applications, such as creating breakthrough products and services or new ways to optimize the supply chain.
  3. Experiment with real quantum systems. Demystify quantum computing by trying out a real quantum computer (IBM’s Q Experience). Have your champions get a sense for how quantum computing may solve your business problems and interface with your existing tools. A quantum solution may not be a fit for every business issue. Your champions will need to focus on solutions to address your highest priority use cases, ones that conventional computers can’t practically solve.
  4. Chart your quantum course. This entails constructing a quantum computing roadmap with viable next steps for the purpose of pursuing problems that could create formidable competitive barriers or enable sustainable business advantage. To accelerate your organization’s quantum readiness, consider joining an emerging quantum community. This can help you gain better access to technical infrastructure, evolving industry applications, and expertise that can enhance your development of specific quantum applications.
  5. Lastly, be flexible about your quantum future. Quantum computing is rapidly evolving. Seek out technologies and development toolkits that are becoming the industry standard, those around which ecosystems are coalescing. Realize that new breakthroughs may cause you to adjust your approach to your quantum development process, including changing your ecosystem partners. Similarly, your own quantum computing needs may evolve over time, particularly as you improve your understanding of which business issues can benefit most from quantum solutions.

Finally, actually have people in your organization try a quantum computer, such as through IBM’s Q program and Qiskit, a free development tool. Q provides a free 16-qubit quantum computer you don’t have to configure or keep cool and stable. That’s IBM’s headache.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at technologywriter.com.

Syncsort Drives IBMi Security with AI

May 2, 2019

The technology security landscape looks increasingly dangerous  The problem revolves around the possible impact of AI. the impact of which is not fully clear. The hope, of course, is that AI will make security more efficient and effective.  However, the security bad actors can also jump on AI to advance their own schemes. Like a cyber version of the nuclear arms race, this has been an ongoing battle for decades. The industry has to cooperate and, specifically, share information and hope the good guys can stay a step ahead.

In the meantime, vendors like IBM and most recently Syncsort have been stepping up to  the latest challengers. Syncsort, for example, earlier this month launched its Assure Security to address the increasing sophistication of cyber attacks and expanding data privacy regulations.  In surprising ways, it turns out, data privacy and AI are closely related in the AI security battle.

Syncsort, a leader in Big Iron-to-Big Data software, announced Assure Security, which combines access control, data privacy, compliance monitoring, and risk assessment into a single product. Together, these capabilities help security officers, IBMi administrators, and Db2 administrators address critical security challenges and comply with new regulations meant to safeguard and protect the privacy of data.

And it clearly is coming at the right time.  According to Privacy Rights Clearinghouse, a non-profit corporation with a mission to advocate for data privacy there were 828 reported security incidents in 2018 resulting in the exposure of over 1.37 billion records of sensitive data. As regulations to help protect consumer and business data become stricter and more numerous, organizations must build more robust data governance and security programs to keep the data from being exploited by bad security actors for nefarious purposes.  The industry already has scrambled to comply with GDPR and the New York Department of Financial Services Cybersecurity regulations and they now must prepare for the GDPR-like California Consumer Privacy Act, which takes effect January 1, 2020.

In its own survey Syncsort found security is the number one priority among IT pros with IBMi systems. “Given the increasing sophistication of cyber attacks, it’s not surprising 41 percent of respondents reported their company experienced a security breach and 20 percent more were unsure if they even had been breached,” said David Hodgson, CPO, Syncsort. The company’s new Assure Security product leverages the wealth of IBMi security technology and the expertise to help organizations address their highest-priority challenges. This includes protecting against vulnerabilities introduced by new, open-source methods of connecting to IBMi systems, adopting new cloud services, and complying with expanded government regulations.

Of course, IBM hasn’t been sleeping through this. The company continues to push various permutations of Watson to tackle the AI security challenge. For example, IBM leverages AI to gather insights and use reasoning to identify relationships between threats, such as malicious files, suspicious IP addresses,  or even insiders. This analysis takes seconds or minutes, allowing security analysts to respond to threats up to 60 times faster.

It also relies on AI to eliminate time-consuming research tasks and provides curated analysis of risks, which reduces the amount of time security analysts require to make the critical decisions and launch an orchestrated response to counter each threat. The result, which IBM refers to as cognitive security, combines the strengths of artificial intelligence and human intelligence.

Cognitive AI in effect, learns with each interaction to proactively detect and analyze threats and provides actionable insights to security analysts making informed decisions. Such cognitive security, let’s hope, combines the strengths of artificial intelligence with human judgement.

Syncsort’s Assure Security, specifically brings together best-in-class IBMi security capabilities acquired by Syncsort into an all-in-one solution, with the flexibility for customers to license individual modules. The resulting product includes:

  • Assure  Compliance Monitoring quickly identifies security and compliance issues with real-time alerts and reports on IBMi system activity and database changes.
  • Assure Access Control provides control of access to IBMi systems and their data through a varied bundle of capabilities.
  • Assure Data Privacy protects IBMi data at-rest and in-motion from unauthorized access and theft through a combination of NIST-certified encryption, tokenization, masking, and secure file transfer capabilities.
  • Assure Security Risk Assessment examines over a dozen categories of security values, open ports, power users, and more to address vulnerabilities.

It probably won’t surprise anyone but the AI security situation is not going to be cleared up soon. Expect to see a steady stream of headlines around security hits and misses over the next few years. Just hope will get easier to separate the good guys from the bad actors and the lessons will be clear.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at technologywriter.com.

IBM Revamps V5000

April 5, 2019

On April 2nd IBM announced several key enhancements across the Storwize V5000 portfolio and along with new models. These new models include the V5010E, 5030E and the V5100. The E stands for EXPRESS.) To further complicate the story, it utilizes Broadwell, Intel’s new 14 nanometer die shrink of its Haswell microarchitecture. Broadwell did not completely replace the full range of CPUs from Intel’s previous Haswell microarchitecture but IBM is using it widely in the new V5000 models.

IBM NVMe Flash Core Module

And the results can be impressive. From a scale-out perspective the V5010E supports a single controller configuration, while the V5030E and V5100 both support up to two controller clusters. This provides for a maximum of 392 drives in the V5010E and a massive 1520 drives in either the V5030E or V5100 dual controller clusters. The V5030E includes the Broadwell DE 1.9GHz, 6 core processor in its two canisters. Each canister supports a maximum of 32GB of RAM. Better still, the V5100 boasts a single Skylake 1.7Ghz processor with 8 cores in each canister. RAM is increased to a total of 576GB for the entire controller, or 288GB maximum per canister.

.For the next generation Storwize V5000 platforms IBM encouraging them to be called Gen3. The Gen3 encompasses 8 new MTM (Machine Type Model) based on 3 hardware models, V5010E, V5030E and V5100. The V5100 comes in two models, a hybrid (HDD and Flash) and the All Flash model V5100F. Of these 4 types, each is available with a 1 year or 3 year warranty.

The V5000E models are based on the Gen2 hardware, with various enhancements, including more memory options on the V5010E. The V5100 models are all new hardware and bring same NVMe Flash Core Modules (FCM) that are available on the V7000 and FlashSystem9100 products, completing Core Modules the transition of the Storwize family to all NVMe arrays. If you haven’t seen or heard about IBM’s FCM technology introduced last year to optimize NVMe FCM are a family of high-performance flash drives that utilizes the NVMe protocol, a PCIe Gen3 interface, and high-speed NAND memory to provide high throughput and IOPS and very low latency. FCM is available in 4.8 TB, 9.6 TB, and 19.2 TB capacities. Hardware-based data compression and self-encryption are built in.

The all flash (F) variants of the V5000 can also attach SAS expansions to extend capacity using SAS based Flash drives to allow expansion up to 1520 drives. The drives, however, are not interchangeable with the new FCM drives. The E variants allow attachment of SAS 2.5” and 3.5” HDD drives, with the V5010E expandable to 392 drives and the others up to 1520.

Inbuilt host attachments come in the form of 10GbE ports for iSCSI workloads, with optional 16Gbit FibreChannel (SCSI or FC-NVMe) as well as additional 10GbE or 25GbE iSCSI. The V5100 models can also use the iSER (an iSCSI translation layer for operation over RDMA transports, such as InfiniBand) protocol over the 25GbE ports for clustering capability, with plans to support NVMeF over Ethernet. In terms of cache memory, the V5000E products are expandable up to 64GB per controller (IO Group) and the V5100 can support up to 576GB per controller. Similarly, IBM issued as a statement of direction for all 25GbE port types across the entire Spectrum Virtualize family of products.

As Lloyd Dean, IBM Senior Certified Executive IT Architect noted, the new lineup for the V5000 is impressive; regarding the quantity of drives, and the storage available per model will “blow your mind”. How mind blowing will depend, of course, on your configuration and IBM’s pricing. As usual, IBM talks about affordable and comparative cost and storage efficiency but they usually never state a price. But they did once 3 years ago: List price then for the V5010 was $9,250 including hardware, software and a one-year warranty, according to a published report. Today IBM will likely steer you to cloud pricing, which may or may not be a bargain depending on how the deal is structured and priced. With the cloud, everything is in the details.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at technologywriter.com.

IBM Rides Quantum Volume  to Quantum Advantage

March 19, 2019

Recently IBM announced achieving its’ highest quantum volume to date. Of course, nobody else knows what Quantum Volume is.  Quantum volume is both a measurement and a procedure developed, no surprise here, by IBM to determine how powerful a quantum computer is. Read the May 4 announcement here.

Quantum volume is not just about the number of qubits, although that is one part of it. It also includes both gate and measurement errors, device cross talk, as well as device connectivity and circuit compiler efficiency. According to IBM, the company has doubled the power of its quantum computers annually since 2017.

The upgraded processor will be available for use by developers, researchers, and programmers to explore quantum computing using a real quantum processor at no cost via the IBM Cloud. This offer has been out in various forms since May 2016 as IBM’s Q Experience.

Also announced was a new prototype of a commercial processor, which will be the core for the first IBM Q early-access commercial systems.  Dates have only been hinted at.

IBM’s recently unveiled IBM Q System One quantum computer, with a fourth-generation 20-qubit processor, which has resulted in a Quantum Volume of 16, roughly double that of the current IBM Q 20-qubit device, which have a Quantum Volume of 8.

The Q volume math goes something like this: a variety of factors determine Quantum Volume, including the number of qubits, connectivity, and coherence time, plus accounting for gate and measurement errors, device cross talk, and circuit software compiler efficiency.

In addition to producing the highest Quantum Volume to date, IBM Q System One’s performance reflects some of the lowest error rates IBM has ever measured, with an average 2-qubit gate error less than 2 percent, and its best gate achieving less than a 1 percent error rate. To build a fully-functional, large-scale, universal, fault-tolerant quantum computer, long coherence times and low error rates are required. Otherwise how could you ever be sure of the results?

Quantum Volume is a fundamental performance metric that measures progress in the pursuit of Quantum Advantage, the Quantum Holy Grail—the point at which quantum applications deliver a significant, practical benefit beyond what classical computers alone are capable. To achieve Quantum Advantage in the next decade, IBM believes that the industry will need to continue to double Quantum Volume every year.

Sounds like Moore’s Law all over again. IBM doesn’t deny the comparison. It writes: in 1965, Gordon Moore postulated that the number of components per integrated function would grow exponentially for classical computers. Jump to the new quantum era and IBM notes its Q system progress since 2017 presents a similar early growth pattern, supporting the premise that Quantum Volume will need to double every year and presenting a clear roadmap toward achieving Quantum Advantage.

IBM’s recently unveiled IBM Q System One quantum computer, with a fourth-generation 20-qubit processor, which has produced a Quantum Volume of 16, roughly double that of the current IBM Q 20-qubit IBM Q Network device, which has a Quantum Volume of 8.

Potential use cases, such as precisely simulating battery-cell chemistry for electric vehicles, speeding quadratic derivative models, and many others are already being investigated by IBM Q Network partners. To achieve Quantum Advantage in the 2020s, IBM believes the industry will need to continue doubling Quantum Volume every year.

In time AI should play a role expediting quantum computing.  For that, researchers will need to develop more effective AI that can identify patterns in data otherwise invisible to classical computers.

Until then how should most data centers proceed? IBM researchers suggest 3 initial steps:

  1. Develop quantum algorithms that demonstrate how quantum computers can improve AI classification accuracy.
  1. Improve feature mapping to a scale beyond the reach of the most powerful classical computers
  2. Classify data through the use of short depth circuits, allowing AI applications in the NISQ (noisy intermediate scale quantum) regime and a path forward to achieve quantum advantage for machine learning.

Sounds simple, right? Let DancingDinosaur know how you are progressing.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at technologywriter.com.


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