Z Open Terminal Emulation

You can spend a lot of time working with the Z and not find much new in terminal emulation. But there actually are a few new things, mainly because times change and people work differently, using different devices and doing new things. Sure, it all goes back to the mainframe, but it is a new world.

Terminal emulator screen

Rocket Software’s latest wrinkle in terminal emulation is BlueZone Web, which promises to simplify using the mainframe by enabling users to access host-based applications anywhere and on any type of device. It is part of a broader initiative Rocket calls Open AppDev for Z. From DancingDinosaur’s perspective its strength lies in being Zowe-compliant, an open source development environment from the Open Mainframe Project.This makes IBM Z a valuable open platform for an enterprise DevOps infrastructure.

Zowe is the first open source framework for z/OS. It facilitates DevOps teams to securely manage, control, script and develop on the mainframe like any other cloud platform. Launched in a collaboration of initial contributors IBM, CA Technologies, and Rocket Software, and supported by the Open Mainframe Project. The goal is to cultivate the next generation of mainframe developers, whether or not they have Z experience. Zowe promotes a faster team on-ramp to productivity, collaboration, knowledge sharing, and communication.

This is the critical thing about Zowe: you don’t need Z platform experience. Open source developers and programmers can use a wide range of popular open source tools, languages, and technologies–the tools they already know. Sure it’d be nice to find an experienced zOS developer  but that is increasingly unlikely, making Zowe a much better bet.   

According to the Open Source Project, IBM’s initial contribution to Zowe was an extensible z/OS framework that provides REST-based services and APIs that will allow even inexperienced developers to rapidly use new technology, tools, languages, and modern workflows with z/OS. 

IBM continues to invest in the open source environment through Zowe and other open source initiatives.  Zowe also has help from Rocket Software, which provides a web user interface, and CA, which handles the Command Line Interface. You can find more about zowe here.

IBM introduced Linux, a leading open source technology, to the Z over 20 years ago. In time it has expanded the range of the Z through open-source tools that can be combined with products developed by different communities. This does create unintentional regulatory and security risks. Rocket Open AppDev for Z helps mitigate these risks, offering a solution that provides developers with a package of open tools and languages they want, along with the security, easy management, and support IBM Z customers require.

“We wanted to solve three common customer challenges that have prevented enterprises from leveraging the flexibility and agility of open software within their mainframe environment: user and system programmer experience, security, and version latency,” said Peter Fandel, Rocket’s Product Director of Open Software for Z. “With Rocket Open AppDev for Z, we believe we have provided an innovative secure path forward for our customers,” he adds. Businesses can now extend the mainframe’s capabilities through the adoption of open source software, making IBM Z a valuable platform for their DevOps infrastructure.”

But there is an even bigger question here that Rocket turned to IDC to answer. The question: whether businesses that run mission-critical workloads on IBM Z or IBMi should remain on these platforms and modernize them by leveraging the innovative tools that exist today or replatform by moving to an alternative on-premises solution, typically x86 or the cloud.

IDC investigated more than 440 businesses that have either modernized the IBM Z or IBMi or replatformed. The results: modernizers incur lower costs for their modernizing initiative than the replatformers.  Modernizers were more satisfied with the new capabilities of their modernized platform than replatformers; and the modernizers achieved a new baseline for which they paid less in hardware, software, and staffing. There is much more of interest in this study, which DancingDinosaur will explore in the weeks or months ahead.

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

IBM Roadmap for Quantum Computing

IBM started quantum computing in the cloud a few years back by making their small qubit machines available in the cloud and even larger ones now. In mid September, IBM released its quantum computing roadmap to take it from today to million-plus qubit devices. The first benchmark is a 1,000-plus qubit device, IBM Condor, targeted for the end of 2023. Its latest challenge: going beyond what’s possible on conventional computers by running revolutionary applications across industries.

control lots of qubits for long enough with few errors

The key is making quantum computers stable by keeping them cold. To that end IBM is developing a dilution refrigerator larger than any currently available commercially. Such a refrigerator puts IBM on a course toward a million-plus qubit processor. 

The IBM Quantum team builds quantum processors that rely on the mathematics of elementary particles in order to expand its computational capabilities running quantum circuits. The biggest challenge facing IBM’s team today is figuring out how to control large systems of qubits for long enough, and with minimal errors, to run the complex quantum circuits required by future quantum applications.

IBM has been exploring superconducting qubits since the mid-2000s, increasing coherence times and decreasing errors to enable multi-qubit devices in the early 2010s. Continued refinements allowed it to put the first quantum computer in the cloud in 2016. 

Today, IBM maintains more than two dozen stable systems on the IBM Cloud for clients and the general public to experiment on, including the 5-qubit IBM Quantum Canary processor and its 27-qubit IBM Quantum Falcon processor,  on which it recently ran a long enough quantum circuit to declare a Quantum Volume of 64, an IBM created metric. This achievement also incorporated improvements to the compiler, refined calibration of the two-qubit gates, and upgrades to the noise handling and readout based on tweaks to the microwave pulses.

This month IBM quietly released its 65-qubit IBM Quantum Hummingbird processor to its Q Network members. This device features 8:1 readout multiplexing, meaning it combines readout signals from eight qubits into one, reducing the total amount of wiring and components required for readout and improving its ability to scale.

Next year, IBM intends to debut a 127-qubit IBM Quantum Eagle processor. Eagle features several upgrades in order to surpass the 100-qubit milestone: through silicon vias, which allow electrical signals to pass through the substrates to enable smaller device sizes and a reduced signal path and multi-level wiring to effectively fan-out a large density of conventional control signals while protecting the qubits in a separate layer in order to maintain high coherence times. The qubit layout will allow IBM to implement the heavy-hexagonal error-correcting code that its team debuted last year, as it scaled up the number of physical qubits and error-corrected logical qubits.

These design principles established for its smaller processors will set it on a course to release a 433-qubit IBM Quantum Osprey system in 2022. More efficient and denser controls and cryogenic infrastructure will ensure that scaling up the processors doesn’t sacrifice the performance of the individual qubits, introduce further sources of noise, or take too large a footprint.

In 2023, IBM intends to debut the 1,121-qubit Quantum Condor processor, incorporating the lessons learned from previous processors while continuing to lower the critical two-qubit errors so that it can run longer quantum circuits. IBM presents Condor as a milestone that marks its ability to implement error correction and scale up devices while simultaneously complex enough to solve problems that can be solved more efficiently on a quantum computer than on the world’s best supercomputers, achieving the quantum Holy Grail.

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

Pushing Quantum Onto the Cloud

Did you ever imagine the cloud would become your quantum computing platform, a place where you would run complex quantum algorithms requiring significant specialized processing across multi-qubit machines available at a click? But that is exactly what is happening.

IBM started it a few years back by making their small qubit machines available in the cloud and even larger ones now. Today Xanadu is offering 8-qubit or 12-qubit chips, and even a 24-qubit chip in the next month or so, according to the Toronto-based company.

Xanadu quantum processor

As DancingDinosaur has previously reported, there are even more: Google reports a quantum computer lab with five machines and Honeywell has six quantum machines. D-Wave is another along with more startups, including nQ, Quantum Circuits, and Rigetti Computing.

D-Wave is another along with more startups, including nQ, Quantum Circuits, and Rigetti Computing.In September, Xanadu introduced its quantum cloud platform. This allows developers to access its gate-based photonic quantum processors with 8-qubit or 12-qubit chips across the cloud.

Photonics-based quantum machines have certain advantages over other platforms, according to the company. Xanadu’s quantum processors operate at room temperature, not low Kelvin temperatures. They can easily integrate into an existing fiber optic-based telecommunication infrastructure, enabling quantum computers to be networked. It also offers scalability and fault tolerance, owing to error-resistant physical qubits and flexibility in designing error correction codes. Xanadu’s type of qubit is based on squeezed states – a special type of light generated by its own chip-integrated silicon photonic devices, it claims.

DancingDinosaur recommends you check out Xanadu’s documentation and details. It does not have sufficient familiarity with photonics, especially as related to quantum computing, to judge any of the above statements. The company also notes it offers a cross-platform Python library for simulating and executing programs on quantum photonic hardware. Its open source tools are available on GitHub.

Late in August IBM has unveiled a new milestone on its quantum computing road map, achieving the company’s highest Quantum Volume to date. By following the link, you see that Quantum Value is a metric conceived by IBM to measure and compare quantum computing power. DancingDinosaur is not aware of any other quantum computing vendors using it, which doesn’t mean anything of course. Quantum computing is so new and so different and with many players joining in with different approaches it will be years before anadu see what metrics prove most useful. 

To come up with its Quantum Volume rating, IBM  combined a series of new software and hardware techniques to improve overall performance, IBM has upgraded one of its newest 27-qubit, systems to achieve the high Quantum Volume rating. The company has made a total of 28 quantum computers available over the last four years through the IBM Quantum Experience, which companies join to gain access to its quantum machines and tools, including its software development toolset, 

Do not confuse Quantum Volume with Quantum Advantage, the point where certain information processing tasks can be performed more efficiently or cost effectively on a quantum computer versus a conventional one. Quantum Advantage will require improved quantum circuits, the building blocks of quantum applications. Quantum Volume, notes IBM, measures the length and complexity of circuits – the higher the Quantum Volume, the higher the potential for exploring solutions to real world problems across industry, government, and research.

To achieve its Quantum Volume milestone, the company focused on a new set of techniques and improvements that used knowledge of the hardware to optimally run the Quantum Volume circuits. These hardware-aware methods are extensible and will improve any quantum circuit run on any IBM Quantum system, resulting in improvements to the experiments and applications which users can explore. These techniques will be available in upcoming releases and improvements to the IBM Cloud software services and the cross-platform open source software development kit (SDK) Qiskit. The IBM Quantum team has shared details on the technical improvements made across the full stack to reach Quantum Volume 64 in a preprint released on arXiv, today.

What is most exciting is that the latest quantum happenings are things quantum you can access over the cloud without having to cool your data center to near zero Kelvin temperatures. If you try any of these, DancingDinosaur would love to hear how it goes.

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

5G Will Accelerate a New Wave of IoT Applications and Z

Even before the advent of 5G DancingDinosaur, which had ghostwritten a top book on IoT, believed that IoT and smartphones would lead back to the Z eventually, somehow. Maybe the arrival of 5G and smart edge computing might slow the path to the Z. Or maybe not.

Even transactions and data originating and being processed at the edge will need to be secured, backed up, stored, distributed to the cloud, to other servers and systems, to multiple clouds, on premises, and further  processed and reprocessed in numerous ways. Along the way, they will find their ways back to a Z somehow and somewhere, sooner or later.

an edge architecture

“5G is driving change in the Internet of Things (IoT). It’s a powerful enabling technology for a new generation of use cases that will leverage edge computing to make IoT more effective and efficient,” writes Rishi Vaish and Sky Matthews. Rishi Vaish is CTO and VP, IBM AI Applications; Sky Matthews is CTO, Engineering Lifecycle Management at IBM.  DancingDinosaur completely agrees, adding only that it won’t just stop there.

Vaish and Matthews continue: “In many ways, the narrative of 5G is the interaction between two inexorable forces: the rise in highly reliable, high-bandwidth communications, and the rapid spread of available computing power throughout the network. The computing power doesn’t just end at the network, though. End-point devices that connect to the network are also getting smarter and more powerful.” 

True enough, the power does not just end there; neither does it start there. There is a long line of powerful systems, the z15 and generations of Z before it that handle and enhance everything that happens in whatever ways are desired at that moment or, as is often the case, later. 

And yes, there will be numerous ways to create comparable services using similarly smart and flexible edge devices. But experience has shown that it takes time to work out the inevitable kinks that invariably will surface, often at the least expected and most inopportune moment. Think of it as just the latest manifestation of Murphy’s Law moved to the edge and 5G.

The increasingly dynamic and powerful computational environment that’s taking shape as telcos begin to redesign their networks for 5G will accelerate the uptake of IoT applications and services throughout industry,  Vaish and Matthews continue. We expect that 5G will enable new use cases in remote monitoring and visual inspection, autonomous operations in large-scale remote environments such as mines, connected vehicles, and more.

This rapidly expanding range of computing options, they add,  requires a much more flexible approach to building and deploying applications and AI models that can take advantage of the most cost-efficient compute resources available.

IBM chimes in: There are many ways that this combination of 5G and edge computing can enable new applications and new innovations in various industries. IBM and Verizon, for example, are developing potential 5G and edge solutions like remote-controlled robotics, near real-time video analysis, and other kinds of factory-floor automation.

The advantage comes from smart 5G edge devices doing the analytics immediately, at the spot where decisions may be best made. Are you sure that decisions made at the edge immediately are always the best? DancingDinosaur would like to see a little more data on that.

In that case, don’t be surprised to discover that there will be other decisions that benefit from being made later, with the addition of other data and analysis. There is too much added value and insight packed into the Z data center to not take advantage of it.

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

AI Hardware Accelerators and AI Models

At times it seems like IBM is just dallying with AI, but at a late July briefing IBM showed just how seriously it is pursuing AI and how difficult the challenge is. It starts with today’s computers and supercomputers, essentially bit processors. Can we say that’s the easy stuff; at least that’s the stuff we are most familiar with.

Neurons come next in the IBM scheme. Here biology and information are tapped for today’s rudimentary AI systems. Next you throw in qubits, which combine physics and information. Now we’re entering the realm of quantum machines.

DancingDinosaur is mesmerized by quantum computing but only understands it at the level of his 40-year old physics course. It starts with today’s computers and supercomputers, essentially bit processors. Can we say this is the easy stuff; at least that’s the stuff we are most familiar with.

Where all this is going is not toward some mesmerizing future of quantum systems dazzling us with nearly instant solutions to seemingly impossible problems. No, it seems, at one level, more prosaic than that, according to Jeffrey Burns.  IBM’s Director, AI Compute.

As Burns  puts it: IBM is building the future of computing. That future, he continues, is a pipeline of innovation for the future of Hybrid Cloud and AI. We should have known that except various IBMers have been saying it for several years at least and it just sounded too simple.

Burns breaks it down into four areas: Core Technology, Innovation for AI, Innovation for Hybrid Cloud, and Foundational Scientific Discovery. 

It is tempting to jump right to the Foundational Scientific Discovery stuff; that’s the sexy part. It includes new devices and materials, breakthrough data communications, computational, secured storage, and  persistent memory architectures.

At the other end is what Burns calls core technology. This encompasses semiconductor devices, processor architecture,  novel memory, MRAM, and advanced packaging.

Among the innovations for AI are AI hardware, real-time AI for transaction processing,  HW and SW for federated AI learning to enhance security and privacy.

Finally, there are innovations for hybrid cloud. These include Red Hat RHEL integration,  storage and data recovery,  high speed networking,  security, and heterogeneous system architecture for hybrid cloud.  

But, AI and Hybrid Cloud can advance only as far as hardware can take them, notes Burns. The processing demands at even the first two steps are significant. For example image recognition training with a dataset of 22K requires 4 GPUs, takes 16 days, and consumes 385 kWh. If you want it faster, you can throw 256 GPUs at it for 7 hours, which still consumes 450 kWh. Or think of it another way, he suggests: 1 model training run eats the equivalent of ~2 weeks of home energy consumption.

And we’ve just been talking about narrow AI. Broad AI, Burns continues, brings even more computational demands and greater functionality requirements at the edge.If you’re thinking of trying this with your data center, none of this is trivial. Last year IBM invested $2B  to create an  Artificial Intelligence Hardware Center. Twelve organizations have joined it and it continues to grow, Burns reports. You’re welcome to join.

IBM’s idea is to innovate and lead in AI accelerators for training and inferencing, leverage partnerships to drive AI leadership from materials and devices through software, and generate AI application demonstrators with an industry leading roadmap. 

Here is where Burns wants to take it: Extending performance by 2.5X/year through 2025.  Apply approximate computing principles to Digital AI cores with reduced precision, as well as Analog AI Cores (Remember analog? Burns sees it playing a big energy-saving role.), which could potentially offer another 100x in energy-efficiency.

If you want to try your hand at AI at this level, DancingDinosaur would love to know and throw some digital ink your way.

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

IBM Elastic Storage System 5000–AI Utility Storage Option

The newest storage from IBM is the Elastic Storage System 5000. It promises, as  you would expect, leading performance, density, and scalability, but that’s not the most interesting part of IBM’s July and Aug. storage offerings. In conjunction with the new storage hardware, IBM is tapping AI through IBM Storage Spectrum, a familiar product to create a smart utility storage option. This allows you to define your current and future storage needs on day one, deploy it all that day while paying only for the capacity you are actually using and activate more only when you need it, paying for it only when you have activated it.

AI Elastic Storage Systems via Spectrum 

Will that save you much money? Maybe, but what it mainly will save you is time. That comes from not having to go through the entire process of ordering and installing the extra capacity. DancingDinosaur guesses it will save you money if you usually over-ordered what you needed initially and paid for it then. IBM says some customers actually do that, but certainly there is no good reason to ever do that–paying for it in advance–at least no longer.

Yes, data volumes continue to grow at explosive rates. And yes, a prudent IT manager does not want to suddenly find the company in a position when a lack of sufficient storage is constraining the performance of critical applications. 

But a prudent data center manager should never be in that position. DancingDinosaur was always taught that the selective use of data compression can free up some top tier storage capacity, even on very short notice. And who doesn’t also have at least a few old storage arrays hanging around that can’t be put back into use to ease a sudden crunch, even if only briefly? OK, it won’t be the fastest or best storage but it could work for a short time at least.

Of course, IBM puts a somewhat different spin on the situation. It explains: For the last 30 years, the standard method has been for organizations to calculate their current application capacity needs and then guess the rest—hoping the guess is enough to meet future needs. The organization then works up an RFQ, RFP or some other tortuous procurement method to get the capacity they need as quickly as possible. The organization then invites all the vendors it knows and some it doesn’t to pitch their solution—at which point the organization usually finds it will need much more capacity than originally thought—or budgeted. 

And IBM continues: Then, only a few months later, the organization realizes its needs have changed—and that what it originally requested is no longer adequate. A year past the initial start, your new capacity is finally in place—and the organization hopes it won’t have to go through the same process again next year. 

Does that sound like you? DancingDinosaur hopes not, at least not in 2020. 

Maybe if your storage environment is large, one with more than 250 TB of storage and is growing, IBM notes. And depending how you specified it initially, additional capacity through its elastic storage program, is instantly available by simply provisioning what you need. From a billing standpoint, it allows you to move what would otherwise be high upfront costs to a predictable quarterly charge directly related to your business activity.

DancingDinosaur has long felt that IBM Spectrum Storage delivered a nifty set of capabilities even before AI became a current fad. If you can take advantage of it to shortcut the storage acquisition and provisioning process while holding onto a few bucks for a little longer what’s not to like. 

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

AI Powered Enterprise

IBM has been proclaiming the power of AI for several years. It has not, however, shown much of it in action. A customer reference here and there, but mostly it takes the form of hints of great capabilities coming at some point. 

At first DancingDinosuar feared Seth Earley was following IBM down the AI vagueness path. Then I received an early copy of his book and the table of contents alone had more tangible descriptions than we’ve seen from IBM in a year. For instance, Chapter 7: Customer Service: Delivering Higher Quality at a Lower Cost; Chapter 8: Accelerating Employee Productivity; Chapter 9: Physical Meets Digital; Manufacturing, Supply Chain, and Logistics.

That’s not to say that Earley can’t get mushy like IBM.  AI is “reinventing the way we invent” and “will usher in a new era of human capabilities.” Or,  “We are at an inflection point in human history,” he says early at the start of his new book, The AI Powered Enterprise, published by LifeTree Media Ltd. But just a few pages in we should be able to cut him some slack; he needs some puffy sound bytes to grab the reviewers or marketing suits, and we know how they dumb down complex technology in their hope to make it more accessible.

So, what can Earley talk about that is different from what we get from IBM’s suits. It starts in the Forward; “The book is heavily focused on the importance of ontologies in conversational AI systems, and ontologies were also very important in knowledge management,” writes Thomas H. Davenport, President’s Distinguished Professor at Babson College, Research Fellow at MIT Initiative on the Digital Economy. He continues: “I do not know of any books that have such useful and detailed advice on the relationship between data and successful conversational AI systems.”

DancingDinosaur was dearly hoping to not write about ontologies, a subject he resorted to taking pass-fail decades ago as an undergraduate. But it can’t be avoided.  Writes Earley “AI needs the key that unlocks that understanding as an ontology; a representation of what matters within the company and makes it unique, including products and services, solutions and processes, organizational structures, protocols, customer characteristics, manufacturing methods, knowledge, content, and data of all types…Simply put, an ontology reveals what is going on inside your business— it’s the DNA of the enterprise.”

Earley then cites a company desperately needing effective search capabilities. It had one but in practice, the navigation within the system was poorly organized, topic areas were unclear or ambiguous, content was not properly labeled or tagged, and search operated so poorly that some workers joked of it as a “random document generator” when the same search entered at different times could produce different results. 

Earley describes the revamp of the search. All aspects of the business and its core knowledge were redeveloped from the foundation up. The blueprints for the new development began with, you guessed it, ontologies and a knowledge architecture. The resulting overhaul led to increases in user satisfaction (from 20% to 80% approval), greater trust in the system, and more.

And Earley is not done yet with ontologies. As the search example showed, ontologies are the DNA of the enterprise… a consistent representation of data and data relationships that can inform and power AI technologies. In different contexts, it can be expressed as any of the following–stuff we’re all familiar with:  a data model, a content model, an information model, a data/content/information architecture, master data, or metadata… an ontology is not a single, static thing; he writes, it is never complete, and it changes as the organization changes and as it is applied throughout the enterprise. The ontology is the master knowledge scaffolding of the organization.” 

IBM improved at describing AI lately. It has Watson and builds and deploys AI learning, manages machine learning models, AI concepts, and more. You can find a slew of IBM AI and machine learning offerings here. 

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 IBV Sees Shift in Pandemic Consumer Attitude

Do you wonder how this pandemic is going to end? Or when. Or what the world will be like when it actually does or if it does, and how we will even know.

IBM quantum computing researcher

IBM’s Institute of Business Value (IBV), an IBM research group, was asking similar questions. It polled more than 18,000 U.S. adults in May and early June to understand how COVID-19 has affected their perspectives on topics that include remote work; the return to the workplace; where they want to live; how they want to shop; and more. 

IBV’s results are not exactly encouraging. For example, it found that consumers are preparing themselves for more permanent changes in behavior because of the pandemic and their fears about future outbreaks. Two of every three respondents said they were concerned about a second wave of COVID-19 hitting later in 2020. More than 60 percent said they believed there were likely to be more global pandemic events like COVID-19 in the future.

The research also suggests that organizations in every industry must pay attention to their customers’ shifting preferences. And they must respond with agility: by adopting technology, rethinking processes and, most importantly, addressing culture in order to emerge from the pandemic smarter and stronger, say the researchers.

DancingDinosaur is not nearly as methodical as the researchers at IBV. But having spent nearly four months being bombarded with solicitations for almost anything that can be squeezed into Zoom I have been able to form some opinions. The first is how ingenious and creative a lot of marketers have become in repackaging their previously tedious messages for what has almost overnight emerged as a virtual Zoom-like world. 

For decades DancingDinosaur has dodged meetings like a plague, or maybe a pandemic. But some have managed to tease me into attending a few virtual zooms, which, surprisingly, were informative and useful and concise. When the pandemic is finally done and gone, marketers may never get DancingDinosaur into a convention center or seminar venue again. Not when it is so easy to click in and, as importantly, how convenient it is to click leave the meeting.

IBV’s research appears to have uncovered some interesting behaviors. For instance, nearly one in five urban residents indicated they would definitely relocate or would consider moving to suburban or rural areas as a result of the pandemic. Fewer than 1 in 10 indicated they now found living in an urban area more appealing. 

That makes sense. If DancingDinosaur was quarantined in a 1 bedroom or studio condo for weeks or months he’d never do that again and hope you wouldn’t either, no matter how tempting the restaurants might have been when you could actually go into them.

Another set of IBV data points bodes badly for combating climate change. Young climate change activist Greta Thunberg, please forgive them. The researchers found 25 percent of respondents said they would use their personal vehicles exclusively as their mode of transport, and an additional 17 percent said they’d use them more than before. A full 60 percent of those who want to use a personal vehicle but don’t own one said they would buy one. The remainder in this group said they would rent a vehicle until they felt safe using shared mobility.

IBV also looked at work-from-home. Before COVID-19 containment measures went into effect, less than 11% of respondents worked from home. As of June 4, that percentage had grown to more than 45%. What’s more, 81% of respondents—up from 75% in April—indicated they want to continue working remotely at least some of the time.  More than half—61%—would like this to become their primary way of working. 

DancingDinosaur spent his entire career working from home. It can be a great life. Of course,  I didn’t have to educate my children at home or on short notice with minimal guidance. They went to public school and summer camp. When they came home from school each day, it made a great excuse for me to take a cookie break with them. I do miss not having my cookie break partners. They married great guys and, if I set any kind of proper example, they now have cookie breaks with them instead.

Alan Radding is DancingDinosaur, a veteran information technology analyst, writer, and ghost-writer still working from home in the Boston area. Follow DancingDinosaur on Twitter, @mainframeblog, and see more of his work at http://technologywriter.com/ 

IBM Wazi cloud-native devops for Z

In this rapidly evolving world of hybrid and multicloud systems, organizations are required to quickly evolve their processes and tooling to address business needs. Foremost among that are development environments that include IBM Z as part of their hybrid solution face, says Sanjay Chandru, Director, IBM Z DevOps.

IBM’s goal, then  is to provide a cloud native developer experience for the IBM Z that is consistent and familiar to all developers. And that requires cross platform consistency in tooling for application programmers on Z who will need to deliver innovation faster and without the backlogs that have been expected in the past.

Wazi, along with OpenShift,  is another dividend from IBM purchase of Red Hat. Here is where IBM Wazi for Red Hat CodeReady Workspaces comes in: an add-on to IBM Cloud Pak for Applications. It allows developers to use an industry standard integrated development environment (IDE),  such as Microsoft Visual Studio Code (VS Code) or Eclipse, to develop and test IBM z/OS applications in a containerized, virtual z/OS environment on Red Hat OpenShift running on x86 hardware. The container creates a sandbox. 

The combination of IBM Cloud Pak for Applications goes beyond what Zowe offers as an open source framework for z/OS and the OpenProject to enable Z development and operations teams to securely manage, control, script and develop on the mainframe like any other cloud platform. Developers who are not used to z/OS and IBM Z, which are most developers, now can  become productive faster in a familiar and accessible working environment, effectively  improving DevOps adoption across the enterprise

As IBM explained: Wazi integrates seamlessly into a standard, Git-based open tool chain to enable continuous integration and continuous delivery (CI/CD) as part of a fully hybrid devops process encompassing distributed and z systems.

IBM continues: Wazi is offered with deployment choices so that organizations can flexibly rebalance entitlement over time based on its business needs. In short, the organization can 

protect and leverage its IBM Z investments with robust and standard development capabilities that encompasses IBM Z and multicloud platforms.

The payoff comes as developers who are NOT used to z/OS and IBM Z, which is most of the developer world, can become productive faster in a familiar and accessible working environment while  improving DevOps adoption across the enterprise. IBM Wazi integrates seamlessly into a standard, Git-based open tool chain to deliver CI/CD and is offered with deployment choices so that any organization can flexibly rebalance over time based on its business needs. In short, you are protecting and leveraging your IBM Z investments with robust and standard development capabilities that encompass the Z and multicloud platforms.

As one large IBM customer put it: “We want to make the mainframe accessible. Use whatever tool you are comfortable with – Eclipse / IDz / Visual Studio Code. All of these things we are interested in to accelerate our innovation on the mainframe” 

An IT service provider added in IBM’s Wazi announcement: “Our colleagues in software development have been screaming for years for a dedicated testing environment that can be created and destroyed rapidly.” Well, now they have it in Wazi.

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