Posts Tagged ‘mainframe’

No letup by IBM on Blockchain

April 27, 2017

IBM continues to push blockchain. Its latest announcement on the subject, Three Blockchain Adoption Principles Essential for Every CEO, came early this week. The basic pitch: in certain market segments blockchain could potentially help save billions of dollars annually and significantly reduce delays and spoilage. Citing the World Economic Forum, the company adds: “reducing barriers within the international supply chain could increase worldwide GDP by almost five percent and total trade volume by 15 percent.”  That should be sweet music to any C-suite exec.

Blockchain enables transparent food chain

In a related announcement also this week, IBM Japan, Mizuho Financial Group, and Mizuho Bank are building a blockchain-based trade financing platform for trade financing. With the platform, Mizuho is aiming to streamline trading operations and improve supply chain efficiency. The resulting timely and highly secure exchange of trade documents turns out to be essential for stakeholders in the supply chain ecosystem. Digitizing trade information on a blockchain can help alter the way information is shared, infusing greater trust into transactions, making it easier for parties involved in the supply chain, including exporters, importers, shippers, insurance companies, port operators, and port authorities to share critical shipment data in near real-time.

IBM is emerging as a leader in secure open-source blockchain solutions built for the enterprise. An early member of the Linux Foundation’s Hyperledger Project, the company has worked with more than 400 clients across multiple business segments to implement blockchain applications delivered via the IBM Cloud.

DancingDinosaur has its own 3 reasons enterprise data center execs should be excited by blockchain. They are different and more z-centric than IBM’s. First, you probably already have a z System, and the z’s legendary security, availability, and scalability make it a natural for blockchain. Second, the z already comes optimized to handle transactions and most of your transaction data already lives on the z, making it very efficient from a processing standpoint.  Third, until or unless your blockchain grows to some enormous size, it will barely consume any system resources or generate overhead. In that sense, blockchain on your z comes virtually free.

The following blockchain principles are based on IBM’s customer experience:

  1. Blockchain has the potential to transform trade, transactions and business processes: The two concepts underpinning blockchain are “business network” and “ledger.” Taken together, these are what make blockchain a smart, tamper-resistant way to conduct trade, transactions and business processes. Network members exchange assets through a ledger that all members can access and share. The ledger syncs across the network with all members needing to confirm a transaction of tangible or intangible assets before it is approved and stored on the blockchain. This shared view helps establish legitimacy and transparency, even when parties are not familiar with one another.
  2. The value, it turns out, resides in the ecosystem as the blockchain network grows: This should be no surprise to an exec who saw the growth, first of LANs and WANs, and later the Internet and Web. So too, as a business network blockchain can include several different types of participants. Depending on the number of participants in a blockchain network, the value of assets being exchanged, and the need to authorize members with varying credentials adopters should observe the difference between “permissioned” and “permission-less” blockchain networks. The real value for blockchain is achieved when these business networks grow. With a strong ecosystem, blockchain networks can more easily reach critical mass, allowing the users to build new business models and reinvent and automate transaction processes.
  3. Blockchain can significantly improve visibility and trust across business: Block chains can reduce transaction settlement times from days or weeks to seconds by providing immediate visibility to all participants. The technology can also be used to cut excess costs by removing intermediary third-parties, those typically required to verify transactions. Because blockchain is built on the concept of trust, it can help reduce risks of illicit practices carried out over payment networks, helping to mitigate fraud and cybercrimes. Speed, cost efficiency, and transparency are among blockchain’s most significant benefits in the enterprise and within ecosystems of companies conducting trade. IBM, Walmart and Tsinghua University, for example, are exploring the use of blockchain to help address the challenges surrounding food safety [see graphic above]. By allowing members within the supply chain to see the same records, blockchain helps narrow down the source of a contamination

“Critical success factors in blockchain engagements require top-down executive support for innovative use cases and bringing key network participants into the dialogue from the start,” according to Marie Wieck, general manager, IBM Blockchain.

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 Gets Serious About Open Data Science (ODS) with Anaconda

April 21, 2017

As IBM rapidly ramps up cognitive systems in various forms, its two remaining platforms, z System and POWER, get more and more interesting. This week IBM announced it was bringing the Anaconda Open Data Science (ODS) platform to its Cognitive Systems and PowerAI.

Anaconda, Courtesy Pinterest

Specifically, Anaconda will integrate with the PowerAI software distribution for machine learning (ML) and deep learning (DL). The goal: make it simple and fast to take advantage of Power performance and GPU optimization for data-intensive cognitive workloads.

“Anaconda on IBM Cognitive Systems empowers developers and data scientists to build and deploy deep learning applications that are ready to scale,” said Bob Picciano, senior vice president of IBM Cognitive Systems. Added Travis Oliphant, co-founder and chief data scientist, Continuum Analytics, which introduced the Anaconda platform: “By optimizing Anaconda on Power, developers will also gain access to the libraries in the PowerAI Platform for exploration and deployment in Anaconda Enterprise.”

With more than 16 million downloads to date, Anaconda has emerged as the Open Data Science platform leader. It is empowering leading businesses across industries worldwide with tools to identify patterns in data, uncover key insights, and transform basic data into the intelligence required to solve the world’s most challenging problems.

As one of the fastest growing fields of AI, DL makes it possible to process enormous datasets with millions or even billions of elements and extract useful predictive models. DL is transforming the businesses of leading consumer Web and mobile application companies, and it is catching on with more traditional business.

IBM developed PowerAI to accelerate enterprise adoption of open-source ML and DL frameworks used to build cognitive applications. PowerAI promises to reduce the complexity and risk of deploying these open source frameworks for enterprises on the Power architecture and is tuned for high performance, according to IBM. With PowerAI, organizations also can realize the benefit of enterprise support on IBM Cognitive Systems HPC platforms used in the most demanding commercial, academic, and hyperscale environments

For POWER shops getting into Anaconda, which is based on Python, is straightforward. You need a Power8 with IBM GPU hardware or a Power8 combined with a Nvidia GPU, in effect a Minsky machine. It’s essentially a developer’s tool although ODS proponents see it more broadly, bridging the gap between traditional IT and lines of business, shifting traditional roles, and creating new roles. In short, they envision scientists, mathematicians, engineers, business people, and more getting involved in ODS.

The technology is designed to run on the user’s desktop but is packaged and priced as a cloud subscription with a base package of 20 users. User licenses range from $500 per year to $30,000 per year depending on which bells and whistles you include. The number of options is pretty extensive.

According to IBM, this started with PowerAI to accelerate enterprise adoption of open-source ML/DL learning frameworks used to build cognitive applications. Overall, the open Anaconda platform brings capabilities for large-scale data processing, predictive analytics, and scientific computing to simplify package management and deployment. Developers using open source ML/DL components can use Power as the deployment platform and take advantage of Power optimization and GPU differentiation for NVIDIA.

Not to be left out, IBM noted growing support for the OpenPOWER Foundation, which recently announced the OpenPOWER Machine Learning Work Group (OPMLWG). The new OPMLWG includes members like Google, NVIDIA and Mellanox to provide a forum for collaboration that will help define frameworks for the productive development and deployment of ML solutions using OpenPOWER ecosystem technology. The foundation has also surpassed 300-members, with new participants such as Kinetica, Red Hat, and Toshiba. For traditional enterprise data centers, the future increasingly is pointing toward cognitive in one form or another.

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-Syncsort-Splunk to Boost Mainframe Security

April 6, 2017

The mainframe has proven to be remarkably secure over the years, racking up the highest security certifications available. But there is still room for improvement. Earlier this week Compuware announced Application Audit, a software tool that aims to transform mainframe cybersecurity and compliance through real-time capture of user behavior.

Capturing user behavior, especially in real-time, is seemingly impossible if you have to rely on the data your collect from the various logs and SMF data.  Compuware’s solution, Application Audit, in conjunction with Syncsort and Splunk, fully captures and analyzes start-to-finish mainframe application user behavior.

As Compuware explains: Most enterprises still rely on disparate logs and SMF data from security products such as RACF, CA-ACF2 and CA-Top Secret to piece together user behavior.  This is too slow if you want to capture bad behavior while it’s going on. Some organization try to apply analytics to these logs but that also is too slow. By the time you have collected enough logs to deduce who did what and when the damage may have been done.  Throw in the escalating demands of cross-platform enterprise cybersecurity and increasingly burdensome global compliance mandates you haven’t a chance without an automated tool optimized for this.

Fortunately, the mainframe provides rich and comprehensive session data you can run through and analyze with Application Audit and in conjunction with the organization’s security information and event management (SIEM) systems to more quickly and effectively see what really is happening. Specifically, it can:

  • Detect, investigate, and respond to inappropriate behavior by internal users with access
  • Detect, investigate, and respond to hacked or illegally accessed user accounts
  • Support criminal/legal investigations with complete and credible forensics
  • Fulfill compliance mandates regarding protection of sensitive data

IBM, by the way, is not ignoring the advantages of analytics for z security.  Back in February you read about IBM bringing its cognitive system to the z on DancingDinosaur.  IBM continues to flog cognitive on z for real-time analytics and security; promising to enable faster customer insights, business insights, and systems insights with decisions based on real-time analysis of both current and historical data delivered on an analytics platform designed for availability, optimized for flexibility, and engineered with the highest levels of security. Check out IBM’s full cognitive for z pitch.

The data Compuware and Syncsort collect with Application Audit is particularly valuable for maintaining control of privileged mainframe user accounts. Both private- and public-sector organizations are increasingly concerned about insider threats to both mainframe and non-mainframe systems. Privileged user accounts can be misused by their rightful owners, motivated by everything from financial gain to personal grievances, as well as by malicious outsiders who have illegally acquired the credentials for those accounts. You can imagine what havoc they could wreak.

In addition, with Application Audit Compuware is orchestrating a number of players to deliver the full security picture. Specifically, through collaboration with CorreLog, Syncsort and Splunk, Compuware is enabling enterprise customers to integrate Application Audit’s mainframe intelligence with popular SIEM solutions such as Splunk, IBM QRadar, and HPE Security ArcSight ESM. Additionally, Application Audit provides an out-of-the-box Splunk-based dashboard that delivers value from the start. As Compuware explains, these integrations are particularly useful for discovering and addressing security issues associated with today’s increasingly common composite applications, which have components running on both mainframe and non-mainframe platforms. SIEM integration also ensures that security, compliance and other risk management staff can easily access mainframe-related data in the same manner as they access data from other platforms.

“Effective IT management requires effective monitoring of what is happening for security, cost reduction, capacity planning, service level agreements, compliance, and other purposes,” noted Stu Henderson, Founder and President of the Henderson Group in the Compuware announcement. “This is a major need in an environment where security, technology, budget, and regulatory pressures continue to escalate.”

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 Changes the Economics of Cloud Storage

March 31, 2017

Storage tiering used to be simple: active data went to your best high performance storage, inactive data went to low cost archival storage, and cloud storage filled in for one or whatever else was needed. Unfortunately, today’s emphasis on continuous data analytics, near real-time predictive analytics, and now cognitive has complicated this picture and the corresponding economics of storage.

In response, last week IBM unveiled new additions to the IBM Cloud Object Storage family. The company is offering clients new choices for archival data and a new pricing model to more easily apply intelligence to unpredictable data patterns using analytics and cognitive tools.

Analytics drive new IBM cloud storage pricing

By now, line of business (LOB) managers, having been exhorted to leverage big data and analytics for years, are listening. More recently, the analytics drumbeat has expanded to include not just big data but sexy IoT, predictive analytics, machine learning, and finally cognitive science. The idea of keeping data around for a few months and parking it in a long term archive to never be looked at again until it is finally deleted permanently just isn’t happening as it was supposed to (if it ever did). The failure to permanently remove expired data can become costly from a storage standpoint as well as risky from an e-discovery standpoint.

IBM puts it this way: Businesses typically have to manage across three types of data workloads: “hot” for data that’s frequently accessed and used; “cool” for data that’s infrequently accessed and used; and “cold” for archival data. Cold storage is often defined as cheaper but slower. For example, if a business uses cold storage, it typically has to wait to retrieve and access that data, limiting the ability to rapidly derive analytical or cognitive insights. As a result, there is a tendency to store data in more expensive hot storage.

IBM’s new cloud storage offering, IBM Cloud Object Storage Flex (Flex), uses a “pay as you use” model of storage tiers potentially lowering the price by 53 percent compared to AWS S3 IA1 and 75 percent compared to Azure GRS Cool Tier.2 (See footnotes at the bottom of the IBM press release linked to above. However IBM is not publishing the actual Flex storage prices.) Flex, IBM’s new cloud storage service, promises simplified pricing for clients whose data usage patterns are difficult to predict. Flex promises organizations will benefit from the cost savings of cold storage for rarely accessed data, while maintaining high accessibility to all data.

Of course, you could just lower the cost of storage by permanently removing unneeded data.  Simply insist that the data owners specify an expiration date when you set up the storage initially. When the date arrives in 5, 10, 15 years automatically delete the data. At least that’s how I was taught eons ago. Of course storage costs orders of magnitude less now although storage volumes are orders of magnitude greater and near real-time analytics weren’t in the picture.

Without the actual rates for the different storage tiers you cannot determine how much Storage Flex may save you.  What it will do, however, is make it more convenient to perform analytics on archived data you might otherwise not bother with.  Expect this issue to come up increasingly as IoT ramps up and you are handling more data that doesn’t need hot storage beyond the first few minutes of its arrival.

Finally, the IBM Cloud Object Storage Cold Vault (Cold Vault) service gives clients access to cold storage data on the IBM Cloud and is intended to lead the category for cold data recovery times among its major competitors. Cold Vault joins its existing Standard and Vault tiers to complete a range of IBM cloud storage tiers that are available with expanded expertise and methods via Bluemix and through the IBM Bluemix Garages.

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 Spotlights Blockchain and Hyperledger Fabric at IBM InterCONNECT

March 23, 2017

IBM announced earlier this week Hyperledger Fabric v 1.0 beta, with security for regulated industries, governance tools, and over 1,000 transactions per second possible.  This is represents the first enterprise-ready blockchain service based on the Linux Foundation’s open source Hyperledger Fabric version 1.0. The service enables developers to quickly build and host security-rich production blockchain networks on the IBM Cloud and underpinned by IBM LinuxONE.

Maersk and IBM transform global trade with blockchain

LinuxONE, a dedicated z-based Linux system with as much security as any commercial platform is likely to have, should play a central role in blockchain networks. The machine also delivers all the itys the z is renowned for: scalability, availability, flexibility, manageability, and more.

The Linux Foundation’s open source Hyperledger Fabric v1.0 is being developed by members of the Hyperledger consortium alongside other open source blockchain technologies. The Hyperledger consortium’s Technical Steering Committee recently promoted Fabric from incubator to active state, and it is expected to be available in the coming weeks. It is designed to provide a framework for enterprise-grade blockchain networks that can transact at over 1,000 transactions per second.

Safety and security is everything with blockchain, which means blockchain networks are only as safe as the infrastructures on which they reside, hence the underpinning on LinuxONE. In addition, IBM’s High Security Business Network brings an extremely secure Linux infrastructure that, according to IBM, integrates security from the hardware up through the software stack, specifically designed for enterprise blockchains by providing:

  • Protection from insider attacks – helps safeguard entry points on the network and fight insider threats from anyone with system administrator credentials
  • The industry’s highest certified level of isolation for a commercial system- Evaluation Assurance Level certification of EAL5+ is critical in highly regulated industries such as government, financial services and healthcare, to prevent the leakage of information from one party’s environment to another
  • Secure Service Containers – to help protect code throughout the blockchain application and effectively encapsulating the blockchain into a virtual appliance, denying access even to privileged users
  • Tamper-responsive hardware security modules –to protect encrypted data for storage of cryptographic keys. These modules are certified to FIPS 140-2 Level 4, the highest level of security certification available for cryptographic modules
  • A highly auditable operating environment – comprehensive , immutable log data supports forensics, audit, and compliance

IBM also announced today the first commercially available blockchain governance tools, and new open-source developer tools that automate the steps it takes to build with the Hyperledger Fabric, reportedly speeding the process from weeks to days.

The new blockchain governance tools also make it easy to set up a blockchain network and assign roles and levels of visibility from a single dashboard. They help network members set rules, manage membership, and enforce network compliance once the network is up and running.

This seems straightforward enough. Once setup is initiated, members can determine the rules of the blockchain and share consent when new members request to join the network. In addition, the deployment tool assigns each network a Network Trust Rating of 1 to 100. New network members can view this before joining and determine whether or not they can trust the network enough to participate. Organizations can also take steps to improve their Trust Ratings before moving into production.

To make it easier for developers to translate business needs from concept to actual code, IBM Blockchain includes a new open-source developer tools for the Hyperledger Fabric called Fabric Composer. Fabric Composer promises to help users model business networks, create APIs that integrate with the blockchain network and existing systems of record, and quickly build a user interface. Fabric Composer also automates tasks that traditionally could take weeks, allowing developers to complete them in minutes instead.

IBM Blockchain for Hyperledger Fabric v1.0 is now available through a beta program on IBM Bluemix. Hyperledger Fabric also is available on Docker Hub as an IBM-certified image available for download at no cost.

At this point, IBM has over 25 publicly named Blockchain projects underway. They address everything from carbon asset management to consumer digital ID, post trade derivatives processing, last mile shipping, supply chain food safety, provenance, securities lending, and more seemingly are being added nearly weekly.

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 Introduces First Universal Commercial Quantum Computers

March 9, 2017

A few years ago DancingDinosaur first encountered the possibility of quantum computing. It was presented as a real but distant possibility. This is not something I need to consider I thought at the time.  By the time it is available commercially I will be long retired and probably six feet under. Well, I was wrong.

This week IBM unveiled its IBM Q quantum systems. IBM Q will be leading Watson and blockchain to deliver the most advanced set of services on the IBM Cloud platform. There are organizations using it now, and DancingDinosaur continues to be living and working still.

IBM Quantum Computing scientists Hanhee Paik (left) and Sarah Sheldon (right) examine the hardware inside an open dilution fridge at the IBM Q Lab

As IBM explains: While technologies that currently run on classical (or conventional) computers, such as Watson, can help find patterns and insights buried in vast amounts of existing data, quantum computers will deliver solutions to multi-faceted problems where patterns cannot be seen because the data doesn’t exist and the possibilities that you need to explore are too enormous to ever be processed by conventional computers.

Just don’t retire your z or Power system in favor on an IBM Q yet. As IBM explained at a recent briefing on the quantum computing the IBM Q universal quantum computers will be able to do any type of problem that conventional computers do today. However, many of today’s workloads, like on-line transaction processing, data storage, and web serving will continue to run more efficiently on conventional systems. The most powerful quantum systems of the next decade will be a hybrid of quantum computers with conventional computers to control logic and operations on large amounts of data.

The most immediate use cases will involve molecular dynamics, drug design, and materials. The new quantum machine, for example, will allow the healthcare industry to design more effective drugs faster and at less cost and the chemical industry to develop new and improved materials.

Another familiar use case revolves around optimization in finance and manufacturing. The problem here comes down to computers struggling with optimization involving an exponential number of possibilities. Quantum systems, noted IBM, hold the promise of more accurately finding the most profitable investment portfolio in the financial industry, the most efficient use of resources in manufacturing, and optimal routes for logistics in the transportation and retail industries.

To refresh the basics of quantum computing.  The challenges invariably entail exponential scale. You start with 2 basic ideas; 1) the uncertainty principle, which states that attempting to observe a state in general disturbs it while obtaining only partial information about the state. Or 2) where two systems can exist in an entangled state, causing them to behave in ways that cannot be explained by supposing that each has some state of its own. No more zero or 1 only.

The basic unit of quantum computing is the qubit. Today IBM is making available a 5 qubit system, which is pretty small in the overall scheme of things. Large enough, however, to experiment and test some hypotheses; things start getting interesting at 20 qubits. An inflexion point, IBM researchers noted, occurs around 50 qubits. At 50-100 qubits people can begin to do some serious work.

This past week IBM announced three quantum computing advances: the release of a new API for the IBM Quantum Experience that enables developers and programmers to begin building interfaces between IBM’s existing 5 qubit cloud-based quantum computer and conventional computers, without needing a deep background in quantum physics. You can try the 5 qubit quantum system via IBM’s Quantum Experience on Bluemix here.

IBM also released an upgraded simulator on the IBM Quantum Experience that can model circuits with up to 20 qubits. In the first half of 2017, IBM plans to release a full SDK on the IBM Quantum Experience for users to build simple quantum applications and software programs. Only the publically available 5 qubit quantum system with a web-based graphical user interface now; soon to be upgraded to more qubits.

 IBM Research Frontiers Institute allows participants to explore applications for quantum computing in a consortium dedicated to making IBM’s most ambitious research available to its members.

Finally, the IBM Q Early Access Systems allows the purchase of access to a dedicated quantum system hosted and managed by IBM. Initial system is 15+ qubits, with a fast roadmap promised to 50+ qubits.

“IBM has invested over decades to growing the field of quantum computing and we are committed to expanding access to quantum systems and their powerful capabilities for the science and business communities,” said Arvind Krishna, senior vice president of Hybrid Cloud and director for IBM Research. “We believe that quantum computing promises to be the next major technology that has the potential to drive a new era of innovation across industries.”

Are you ready for quantum computing? Try it today on IBM’s Quantum Experience through Bluemix. Let me know how it works for you.

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 and Northern Trust Collaborate on Blockchain for Private Equity Markets

March 3, 2017

At a briefing for IT analysts, IBM laid out how it sees blockchain working in practice. Surprisingly, the platform for the Hyperledger effort was not x86 but LinuxONE due to its inherent security.  As the initiative grows the z-based LinuxONE can also deliver the performance, scalability, and reliability the effort eventually will need too.

IBM describes its collaboration with Northern Trust and other key stakeholders as the first commercial deployment of blockchain technology for the private equity market. Although as the private equity market stands now the infrastructure supporting private equity has seen little innovation in recent years even as investors seek greater transparency, security, and efficiency. Enter the open LinuxONE platform, the Hyperledger fabric, and Unigestion, a Geneva, Switzerland-based asset manager with $20 billion in assets under management.

IBM Chairman and CEO Ginni Rometty discusses how cognitive technology and innovations such as Watson and blockchain have the potential to radically transform the financial services industry at Sibos 2016 in Geneva, Switzerland on Weds., September 28, 2016. (Feature Photo Service)

IBM Chairman and CEO Ginni Rometty discusses  blockchain at Sibos

The new initiative, as IBM explains it, promises a new and comprehensive way to access and visualize data.  Blockchain captures and stores information about every transaction and investment as meta data. It also captures details about relevant documents and commitments. Hyperledger itself is a logging tool that creates an immutable record.

The Northern Trust effort connects business logic, legacy technology, and blockchain technology using a combination of Java/JavaScript and IBMs blockchain product. It runs on IBM Bluemix (cloud) using IBM’s Blockchain High Security Business Network. It also relies on key management to ensure record/data isolation and enforce geographic jurisdiction. In the end it facilitates managing the fund lifecycle more efficiently than the previous primarily paper-based process.

More interesting to DancingDinosaur is the selection of the z through LinuxONE and blockchain’s use of storage.  To begin with blockchain is not really a database. It is more like a log file, but even that is not quite accurate because “it is a database you play as a team sport,” explained Arijit Das, Senior Vice President, FinTech Solutions, at the analyst briefing. That means you don’t perform any of the usual database functions; no deletes or updates, just appends.

Since blockchain is an open technology, you actually could do it on any x86 Linux machine, but DancingDinosaur readers probably wouldn’t want to do that. Blockchain essentially ends up being a distributed group activity and LinuxONE is unusually well optimized for the necessary security. It also brings scalability, reliability, and high performance along with the rock-solid security of the latest mainframe. In general LinuxONE can handle 8000 virtual servers in a single system and tens of thousands of containers. Try doing that with an x86 machine or even dozens.   You can read more on LinuxONE that DancingDinosaur wrote when it was introduced here and here.

But you won’t need near that scalability with the private equity application, at least at first. Blockchain gets more interesting when you think about storage. Blockchain has the potential to generate massive numbers of files fast, but that will only happen when it is part of, say, a supply chain with hundreds, or more likely, thousands of participating nodes on the chain and those nodes are very active. More likely for private equity trading, certainly at the start, blockchain will handle gigabytes of data and maybe only megabytes at first. This is not going to generate much revenue for IBM storage. A little bit of flash could probably do the trick.

Today, current legal and administrative processes that support private equity are time consuming and expensive, according to Peter Cherecwich, president of Corporate & Institutional Services at Northern Trust. They lack transparency while inefficient market practices leads to lengthy, duplicative and fragmented investment and administration processes. Northern Trust’s solution based on blockchain and Hyperledger, however, promises to deliver a significantly enhanced and efficient approach to private equity administration.

Just don’t expect to see overnight results. In fact, you can expect more inefficiency since the new blockchain/Hyperledger-based system is running in parallel with the disjointed manual processes. Previous legacy systems remain; they are not yet being replaced. Still, IBM insists that blockchain is an ideal technology to bring innovation to the private equity market, allowing Northern Trust to improve traditional business processes at each stage to deliver greater transparency and efficiency. Guess we’ll just have to wait and watch.

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 Launches New IoT Collaborative Initiative

February 23, 2017

Collaboration partners can pull hundreds of millions of dollars in new revenue from IoT, according to IBM’s recent IoT announcement. Having reached what it describes as a tipping point with IoT innovation the company now boasts of having over 6,000 clients and partners around the world, many of whom are now wanting to join in its new global Watson IoT center to co-innovate. Already Avnet, BNP Paribas, Capgemini, and Tech Mahindra will collocate development teams at the IBM Munich center to work on IoT collaborations.

new-ibm-watson-iot-center

IBM Opens New Global Center for Watson IoT

The IBM center also will act as an innovation space for the European IoT standards organization EEBus.  The plan, according to Harriet Green, General Manager, IBM Watson IoT, Cognitive Engagement and Education (pictured above left), calls for building a new global IoT innovation ecosystem that will explore how cognitive and IoT technologies will transform industries and our daily lives.

IoT and more recently cognitive are naturals for the z System, and POWER Systems have been the platform for natural language processing and cognitive since Watson won Jeopardy three years ago. With the latest enhancements IBM has brought to the z in the form of on-premises cognitive and machine learning the z should assume an important role as it gathers, stores, collects, and processes IoT data for cognitive analysis. DancingDinosaur first reported on this late in 2014 and again just last week. As IoT and cognitive workloads ramp up on z don’t be surprised to see monthly workload charges rise.

Late last year IBM announced that car maker BMW will collocate part of its research and development operations at IBM’s new Watson IoT center to help reimagine the driving experience. Now, IBM is announcing four more companies that have signed up to join its special industry “collaboratories” where clients and partners work together with 1,000 Munich-based IBM IoT experts to tap into the latest design thinking and push the boundaries of the possible with IoT.

Let’s look at the four newest participants starting with Avnet. According to IBM, an IT distributor and global IBM partner, Avnet will open a new joint IoT Lab within IBM’s Watson IoT HQ to develop, build, demonstrate and sell IoT solutions powered by IBM Watson. Working closely with IBM’s leading technologists and IoT experts, Avnet also plans to enhance its IoT technical expertise through hands-on training and on-the-job learning. Avnet’s team of IoT and analytics experts will also partner with IBM on joint business development opportunities across multiple industries including smart buildings, smart homes, industry, transportation, medical, and consumer.

As reported by BNP Paribas, Consorsbank, its retail digital bank in Germany, will partner with IBM´s new Watson IoT Center. The company will collocate a team of solution architects, developers and business development personnel at the Watson facility. Together with IBM’s experts, they will explore how IoT and cognitive technologies can drive transformation in the banking industry and help innovate new financial products and services, such as investment advice.

Similarly, global IT consulting and technology services provider Capgemini will collocate a team of cognitive IoT experts at the Watson center. Together they will help customers maximize the potential of Industry 4.0 and develop and take to market sector-specific cognitive IoT solutions. Capgemini plans a close link between its Munich Applied Innovation Exchange and IBM’s new Customer Experience zones to collaborate with clients in an interactive environment.

Finally, the Indian multinational provider of enterprise and communications IT and networking technology Tech Mahindra, is one of IBM’s Global System Integrators with over 3,000 specialists focused on IBM technology around the world. The company will locate a team of six developers and engineers within the Watson IoT HQ to help deliver on Tech Mahindra’s vision of generating substantial new revenue based on IBM’s Watson IoT platform. Tech Mahindra will use the center to co-create and showcase new solutions based on IBM’s Watson IoT platform for Industry 4.0 and Manufacturing, Precision Farming, Healthcare, Insurance and Banking, and automotive.

To facilitate connecting the z to IoT IBM offers a simple recipe. It requires 4 basic ingredients and 4 steps: Texas Instrument’s SensorTag, a Bluemix account, IBM z/OS Connect Enterprise Edition, and a back-end service like CICS.  Start by exposing an existing z Systems application as a RESTful AP. This is where the z/OS Connect Edition comes in.  Then enable your SensorTag device to Watson IoT Quick Start. From there connect the Cloud to your on-premises Hybrid Cloud.  Finally, enable the published IoT data to trigger a RESTful API. Sounds pretty straightforward but—full disclosure—Dancing Dinosaur has not tried it due to lacking the necessary pieces. If you try it, please tell DancingDinosaur how it works (info@radding.net). Good luck.

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.

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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.

 


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